Given the unconstrained characteristics of the multi-robot coordinated towing system,the rope can only provide a unidirectional constraint force to the suspended object,which leads to the weak ability of the system to...Given the unconstrained characteristics of the multi-robot coordinated towing system,the rope can only provide a unidirectional constraint force to the suspended object,which leads to the weak ability of the system to resist external disturbances and makes it difficult to control the trajectory of the suspended object.Based on the kinematics and statics of the multi-robot coordinated towing system with fixed base,the dynamic model of the system is established by using the Newton-Euler equations and the Udwadia-Kalaba equations.To plan the trajectories with high stability and strong control,trajectory planning is performed by combining the dynamics and stability of the towing system.Based on the dynamic stability of the motion trajectory of the suspended object,the stability of the suspended object is effectively improved through online real-time planning and offline manual adjustment.The effectiveness of the proposed method is verified by comparing the motion stability of the suspended object before and after planning.The results provide a foundation for the motion planning and coordinated control of the towing system.展开更多
Unmanned aerial vehicles(UAVs)have attracted growing research interests in recent years,which can be used as cost-effective aerial platforms to transmit collected data packets to ground access points(APs).Thus,it is c...Unmanned aerial vehicles(UAVs)have attracted growing research interests in recent years,which can be used as cost-effective aerial platforms to transmit collected data packets to ground access points(APs).Thus,it is crucial to investigate robust airto-ground(A2G)wireless links for high-speed UAVs.However,the A2G wireless link is unstable as it suffers from large path-loss and severe Doppler effect due to the high mobility of UAVs.In order to meet these challenges,we propose an orthogonal time frequency space(OTFS)-based UAV communication system to relief the Doppler effect.Besides,considering that the energy of UAV is limited,we optimize the trajectory planning of UAV to minimize the energy consumption under the constraints of bit error rate(BER)and transmission rate,where the Doppler compensation is taken into account.Simulation results show that the performance of OTFS-based UAV system is superior to orthogonal frequency division multiplexing(OFDM)-based UAV systems,which can accomplish transmission tasks over shorter distances with lower energy consumption.展开更多
To ensure safe flight of multiple fixed-wing unmanned aerial vehicles(UAVs)formation,considering trajectory planning and formation control together,a leader trajectory planning method based on the sparse A*algorithm i...To ensure safe flight of multiple fixed-wing unmanned aerial vehicles(UAVs)formation,considering trajectory planning and formation control together,a leader trajectory planning method based on the sparse A*algorithm is introduced.Firstly,a formation controller based on prescribed performance theory is designed to control the transient and steady formation configuration,as well as the formation forming time,which not only can form the designated formation configuration but also can guarantee collision avoidance and terrain avoidance theoretically.Next,considering the constraints caused by formation controller on trajectory planning such as the safe distance,turn angle and step length,as well as the constraint of formation shape,a leader trajectory planning method based on sparse A^(*)algorithm is proposed.Simulation results show that the UAV formation can arrive at the destination safely with a short trajectory no matter keeping the formation or encountering formation transformation.展开更多
Rehabilitation robots can help physiatrists to assist patients in improving their movement ability.Due to the interaction between rehabilitation robots and patients,the robots need to complete rehabilitation training ...Rehabilitation robots can help physiatrists to assist patients in improving their movement ability.Due to the interaction between rehabilitation robots and patients,the robots need to complete rehabilitation training on a safe basis.This paper presents an approach for smooth trajectory planning for a cable-driven parallel waist rehabilitation robot(CDPWRR)based on the rehabilitation evaluation factors.First,motion capture technology is used to collect the motion data of several volunteers in waist twisting.Considering the impact of motion variability,the feature points at the center of the human pelvis are obtained after eliminating unreasonable data through rationality judgments.Then,point-to-point waist training trajectory planning based on quintic polynomial and cycloid functions,and multipoint waist training trajectory planning based on quintic B-spline functions are carried out.The corresponding planned curves and kinematics characteristics using three methods are compared and analyzed.Subsequently,the rehabilitation evaluation factors are introduced to conduct smooth trajectory planning for waist training,and the waist trajectory with better compliance is obtained based on the safety and feasibility of waist motion.Finally,the physical prototype of the CDPWRR is built,and the feasibility and effectiveness of the proposed smooth trajectory planning method are proved by numerical analysis and experiments.展开更多
The main aim of future mobile networks is to provide secure,reliable,intelligent,and seamless connectivity.It also enables mobile network operators to ensure their customer’s a better quality of service(QoS).Nowadays...The main aim of future mobile networks is to provide secure,reliable,intelligent,and seamless connectivity.It also enables mobile network operators to ensure their customer’s a better quality of service(QoS).Nowadays,Unmanned Aerial Vehicles(UAVs)are a significant part of the mobile network due to their continuously growing use in various applications.For better coverage,cost-effective,and seamless service connectivity and provisioning,UAVs have emerged as the best choice for telco operators.UAVs can be used as flying base stations,edge servers,and relay nodes in mobile networks.On the other side,Multi-access EdgeComputing(MEC)technology also emerged in the 5G network to provide a better quality of experience(QoE)to users with different QoS requirements.However,UAVs in a mobile network for coverage enhancement and better QoS face several challenges such as trajectory designing,path planning,optimization,QoS assurance,mobilitymanagement,etc.The efficient and proactive path planning and optimization in a highly dynamic environment containing buildings and obstacles are challenging.So,an automated Artificial Intelligence(AI)enabled QoSaware solution is needed for trajectory planning and optimization.Therefore,this work introduces a well-designed AI and MEC-enabled architecture for a UAVs-assisted future network.It has an efficient Deep Reinforcement Learning(DRL)algorithm for real-time and proactive trajectory planning and optimization.It also fulfills QoS-aware service provisioning.A greedypolicy approach is used to maximize the long-term reward for serving more users withQoS.Simulation results reveal the superiority of the proposed DRL mechanism for energy-efficient and QoS-aware trajectory planning over the existing models.展开更多
In this paper,multi-UAV trajectory planning and resource allocation are jointly investigated to improve the information freshness for vehicular networks,where the vehicles collect time-critical traffic information by ...In this paper,multi-UAV trajectory planning and resource allocation are jointly investigated to improve the information freshness for vehicular networks,where the vehicles collect time-critical traffic information by on-board sensors and upload to the UAVs through their allocated spectrum resource.We adopt the expected sum age of information(ESAoI)to measure the network-wide information freshness.ESAoI is jointly affected by both the UAVs trajectory and the resource allocation,which are coupled with each other and make the analysis of ESAoI challenging.To tackle this challenge,we introduce a joint trajectory planning and resource allocation procedure,where the UAVs firstly fly to their destinations and then hover to allocate resource blocks(RBs)during a time-slot.Based on this procedure,we formulate a trajectory planning and resource allocation problem for ESAoI minimization.To solve the mixed integer nonlinear programming(MINLP)problem with hybrid decision variables,we propose a TD3 trajectory planning and Round-robin resource allocation(TTPRRA).Specifically,we exploit the exploration and learning ability of the twin delayed deep deterministic policy gradient algorithm(TD3)for UAVs trajectory planning,and utilize Round Robin rule for the optimal resource allocation.With TTP-RRA,the UAVs obtain their flight velocities by sensing the locations and the age of information(AoI)of the vehicles,then allocate the RBs to the vehicles in a descending order of AoI until the remaining RBs are not sufficient to support another successful uploading.Simulation results demonstrate that TTP-RRA outperforms the baseline approaches in terms of ESAoI and average AoI(AAoI).展开更多
To avoid impacts and vibrations during the processes of acceleration and deceleration while possessing flexible working ways for cable-suspended parallel robots(CSPRs),point-to-point trajectory planning demands an und...To avoid impacts and vibrations during the processes of acceleration and deceleration while possessing flexible working ways for cable-suspended parallel robots(CSPRs),point-to-point trajectory planning demands an under-constrained cable-suspended parallel robot(UCPR)with variable angle and height cable mast as described in this paper.The end-effector of the UCPR with three cables can achieve three translational degrees of freedom(DOFs).The inverse kinematic and dynamic modeling of the UCPR considering the angle and height of cable mast are completed.The motion trajectory of the end-effector comprising six segments is given.The connection points of the trajectory segments(except for point P3 in the X direction)are devised to have zero instantaneous velocities,which ensure that the acceleration has continuity and the planned acceleration curve achieves smooth transition.The trajectory is respectively planned using three algebraic methods,including fifth degree polynomial,cycloid trajectory,and double-S velocity curve.The results indicate that the trajectory planned by fifth degree polynomial method is much closer to the given trajectory of the end-effector.Numerical simulation and experiments are accomplished for the given trajectory based on fifth degree polynomial planning.At the points where the velocity suddenly changes,the length and tension variation curves of the planned and unplanned three cables are compared and analyzed.The OptiTrack motion capture system is adopted to track the end-effector of the UCPR during the experiment.The effectiveness and feasibility of fifth degree polynomial planning are validated.展开更多
A new seam-tracking method based on dynamic trajectory planning for a mobile welding robot is proposed in order to improve the response lag of the mobile robot and the high frequency oscillation in seam-tracking.By us...A new seam-tracking method based on dynamic trajectory planning for a mobile welding robot is proposed in order to improve the response lag of the mobile robot and the high frequency oscillation in seam-tracking.By using a front-placed laser-based vision sensor to dynamically extract the location of the weld seam in front of torch,the trend and direction of the weld line is roughly obtained.The robot system autonomously and dynamically performs trajectory planning based on the isometric approximation model.Arc sensor technology is applied to detect the offset during welding process in real time.The dynamic compensation of the weld path is done in combination with the control of the mobile robot and the executive body installed on it.Simulated and experimental results demonstrate that the method effectively increases the stability of welding speed and smoothness of the weld track,and hence the weld formation in curves and corners is improved.展开更多
Unmanned Aerial Vehicles(UAVs)acting as aerial users to access the cellular network form a promising solution to guarantee its safe and efficient operations via the high-quality communication.Due to the flexible mobil...Unmanned Aerial Vehicles(UAVs)acting as aerial users to access the cellular network form a promising solution to guarantee its safe and efficient operations via the high-quality communication.Due to the flexible mobility of UAVs and the coverage range limits of ground base station(GBS),the signalto-noise ratio(SNR)of the communication link between UAVs and GBS will fluctuate.It is an important requirement to maintain the UAV’s cellular connection to meet a certain SNR requirement during the mission for UAV flying from take off to landing.In this paper,we study an efficient trajectory planning method that can minimize a cellular-connected UAV’s mission completion time under the connectivity requirement.The conventional method to tackle this problem adopts graph theory or a dynamic programming method to optimize the trajectory,which generally incurs high computational complexities.Moreover,there is a nonnegligible performance gap compared to the optimal solution.To this end,we propose an iterative trajectory optimizing algorithm based on geometric planning.Firstly,we apply graph theory to obtain all the possible UAV-GBS association sequences and select the candidate association sequences based on the topological relationship among UAV and GBSs.Next,adopting the triangle inequality property,an iterative handover location design is proposed to determine the shortest flight trajectory with fast convergence and low computation complexity.Then,the best flight trajectory can be obtained by comparing all the candidate trajectories.Lastly,we revealed the tradeoff between mission completion time and flight energy consumption.Numerical results validate that our proposed solution can obtain the effectiveness with set accuracy and outperform against the benchmark schemes with affordable computation time.展开更多
Robot manipulators perform a point-point task under kinematic and dynamic constraints.Due to multi-degreeof-freedom coupling characteristics,it is difficult to find a better desired trajectory.In this paper,a multi-ob...Robot manipulators perform a point-point task under kinematic and dynamic constraints.Due to multi-degreeof-freedom coupling characteristics,it is difficult to find a better desired trajectory.In this paper,a multi-objective trajectory planning approach based on an improved elitist non-dominated sorting genetic algorithm(INSGA-II)is proposed.Trajectory function is planned with a new composite polynomial that by combining of quintic polynomials with cubic Bezier curves.Then,an INSGA-II,by introducing three genetic operators:ranking group selection(RGS),direction-based crossover(DBX)and adaptive precision-controllable mutation(APCM),is developed to optimize travelling time and torque fluctuation.Inverted generational distance,hypervolume and optimizer overhead are selected to evaluate the convergence,diversity and computational effort of algorithms.The optimal solution is determined via fuzzy comprehensive evaluation to obtain the optimal trajectory.Taking a serial-parallel hybrid manipulator as instance,the velocity and acceleration profiles obtained using this composite polynomial are compared with those obtained using a quintic B-spline method.The effectiveness and practicability of the proposed method are verified by simulation results.This research proposes a trajectory optimization method which can offer a better solution with efficiency and stability for a point-to-point task of robot manipulators.展开更多
Aiming at the yaw problem caused by inertial navigation system errors accumulation during the navigation of an intelligent aircraft,a three-dimensional trajectory planning method based on the particle swarm optimizati...Aiming at the yaw problem caused by inertial navigation system errors accumulation during the navigation of an intelligent aircraft,a three-dimensional trajectory planning method based on the particle swarm optimization-A star(PSO-A*)algorithm is designed.Firstly,an environment model for aircraft error correction is established,and the trajectory is discretized to calculate the positioning error.Next,the positioning error is corrected at many preset trajectory points.The shortest trajectory and the fewest correction times are regarded as optimization goals to improve the heuristic function of A star(A*)algorithm.Finally,the index weights are continuously optimized by the particle swarm optimization algorithm.The optimal trajectory is found by the A*algorithm under the current evaluation index,so the ideal trajectory is planned.The experimental results show that the PSO-A*algorithm can quickly search for ideal trajectories in different environment models,indicating that the algorithm has certain feasibility and adaptability,and verifies the rationality of the proposed trajectory planning model.The PSO-A*algorithm has better convergence accuracy than the A*algorithm,and the search efficiency is significantly better than the grid search A star(GS-A*)algorithm.The PSO-A*algorithm proposed in this paper has certain engineering application value.The researchers will study the real-time and systematic nature of the algorithm.展开更多
To accommodate the gait and balance disorder of the elderly with age progression and the occurrence of various senile diseases,this paper proposes a novel gait balance training robot(G-Balance)based on a six degree-of...To accommodate the gait and balance disorder of the elderly with age progression and the occurrence of various senile diseases,this paper proposes a novel gait balance training robot(G-Balance)based on a six degree-of-freedom parallel platform.Using the platform movement and IMU wearable sensors,two training modes,i.e.,active and passive,are developed to achieve vestibular stimulation.Virtual reality technology is applied to achieve visual stimulation.In the active training mode,the elderly actively exercises to control the posture change of the platform and the switching of the virtual scene.In the passive training mode,the platform movement is combined with the virtual scene to simulate bumpy environments,such as earthquakes,to enhance the human anti-interference ability.To achieve a smooth switching of the scene,continuous speed and acceleration of the platform motion are required in some scenarios,in which a trajectory planning algorithm is applied.This paper describes the application of the trajectory planning algorithm in the balance training mode and the optimization of jerk(differential of acceleration)based on cubic spline planning,which can reduce impact on the joint and enhance stability.展开更多
High-speed parallel robots have been extensively utilized in the light industry.However,the influence of the nonlinear dynamic characteristics of high-speed parallel robots on system’s dynamic response and stable ope...High-speed parallel robots have been extensively utilized in the light industry.However,the influence of the nonlinear dynamic characteristics of high-speed parallel robots on system’s dynamic response and stable operation cannot be ignored during the high-speed reciprocating motion.Thus,trajectory planning is essential for efficiency and stability from pick-and-place(PAP)actions.This paper presents a method for planning the equal-height pick-and-place trajectory considering velocity constraints to improve the PAP efficiency and stability of high-speed parallel robots.The velocity constraints in the start-and-end points can reduce vibration from picking and placing,making the trajectory more suitable to complex beltline situations.Based on velocity constraints,trajectory optimization includes trajectory smoothness and joint torque to optimize cycle time is carried out.This paper proposes an online trajectory optimization solution.By using back propagation(BP)neural networks,the solution is simplified and can be solved in real-time.Simulation and experiments were carried out on the SR4 parallel robot.The results show that the proposed method improves the efficiency,smoothness,and stability of the robot.This paper proposes an online trajectory planning method which is velocity constraints based and can improve the efficiency and stability of high-speed parallel robots.The work of this research is conducive to finely applying high-speed parallel robots.展开更多
This paper addresses a major issue in planning the trajectories of under-actuated autonomous vehicles based on neurodynamic optimization.A receding-horizon vehicle trajectory planning task is formulated as a sequentia...This paper addresses a major issue in planning the trajectories of under-actuated autonomous vehicles based on neurodynamic optimization.A receding-horizon vehicle trajectory planning task is formulated as a sequential global optimization problem with weighted quadratic navigation functions and obstacle avoidance constraints based on given vehicle goal configurations.The feasibility of the formulated optimization problem is guaranteed under derived conditions.The optimization problem is sequentially solved via collaborative neurodynamic optimization in a neurodynamics-driven trajectory planning method/procedure.Simulation results with under-actuated unmanned wheeled vehicles and autonomous surface vehicles are elaborated to substantiate the efficacy of the neurodynamics-driven trajectory planning method.展开更多
In this paper,a fast approach to generate time optimal and smooth trajectory has been developed and tested.Minimum time is critical for the productivity in industrial applications.Meanwhile,smooth trajectories based o...In this paper,a fast approach to generate time optimal and smooth trajectory has been developed and tested.Minimum time is critical for the productivity in industrial applications.Meanwhile,smooth trajectories based on cubic splines are desirable for their ability to limit vibrations and ensure the continuity of position,velocity and acceleration during the robot movement.The main feature of the approach is a satisfactory solution that can be obtained by a local modification process among each interval between two consecutive via-points.An analytical formulation simplifies the approach to smooth trajectory and few iterations are enough to determine the correct values.The approach can be applied in many robot manipulators which require high performance on time and smooth.The simulation and application of the approach on a palletizer robot are performed,and the experimental results provide evidence that the approach can realize the robot manipulators more efficiency and high smooth performance.展开更多
This paper investiga tes a trajectory planning algorithm to reduce the manipulator’s working time.A t ime-optimal trajectory planning(TOTP)is conducted based on improved ad aptive genetic algorithm(IAGA)and combined ...This paper investiga tes a trajectory planning algorithm to reduce the manipulator’s working time.A t ime-optimal trajectory planning(TOTP)is conducted based on improved ad aptive genetic algorithm(IAGA)and combined with cubic triangular Bezier spline(CTBS).The CTBS based trajectory planning we did before can achieve continuous second and third derivation,hence it meets the stability requirements of the m anipulator.The working time can be greatly reduced by applying IAGA to the puma 560 trajectory planning when considering physical constraints such as angular ve locity,angular acceleration and jerk.Simulation experiments in both Matlab and ADAMS illustrate that TOTP based on IAGA can give a time optimal result with sm oothness and stability.展开更多
The trend towards automation and intelligence in aircraft final assembly testing has led to a new demand for autonomous perception of unknown cockpit operation scenes in robotic collaborative airborne system testing.T...The trend towards automation and intelligence in aircraft final assembly testing has led to a new demand for autonomous perception of unknown cockpit operation scenes in robotic collaborative airborne system testing.To address this demand,a robotic automated 3D reconstruction cell which enables to autonomously plan the robot end-camera’s trajectory is developed for image acquisition and 3D modeling of the cockpit operation scene.A continuous viewpoint path planning algorithm is proposed that incorporates both 3D reconstruction quality and robot path quality into optimization process.Smoothness metrics for viewpoint position paths and orientation paths are introduced together for the first time in 3D reconstruction.To ensure safe and effective movement,two spatial constraints,Domain of View Admissible Position(DVAP)and Domain of View Admissible Orientation(DVAO),are implemented to account for robot reachability and collision avoidance.By using diffeomorphism mapping,the orientation path is transformed into 3D,consistent with the position path.Both orientation and position paths can be optimized in a unified framework to maximize the gain of reconstruction quality and path smoothness within DVAP and DVAO.The reconstruction cell is capable of automatic data acquisition and fine scene modeling,using the generated robot C-space trajectory.Simulation and physical scene experiments have confirmed the effectiveness of the proposed method to achieve highprecision 3D reconstruction while optimizing robot motion quality.展开更多
This paper is concerned with trajectory planning problems for UAVs operating near ground.Most existing studies focus on solving the problem of collision-free trajectory planning between pre-defined path points,but ign...This paper is concerned with trajectory planning problems for UAVs operating near ground.Most existing studies focus on solving the problem of collision-free trajectory planning between pre-defined path points,but ignore the need of navigation method for UAVs working on specific operating surfaces in near-ground space.In this paper,a novel near-ground trajectory planning framework is proposed,where the hybrid voxel-surfel map is developed to model the environment with special attention to the uneven operating surface.To improve the frequency of updates,a probability-based surfel fusion method and a resolution adaptive adjustment method based on the fusion result are proposed in this paper.By using possibility information in the map,a path search method is established to generate the initial trajectory.The trajectory is then further optimized based on map gradient information to generate a final trajectory that tracks the specified operating surface according to the task requirements.Compared with existing methods,the multi-resolution hybrid voxel-surfel map proposed in this paper has advantages in terms of operating efficiency.A series of experiments in simulated and real scenarios validate the effectiveness of the proposed trajectory planning framework.展开更多
An online trajectory planning method for collision avoidance is proposed to improve vehicle driving safety and comfort simultaneously.The collision-free trajectory for autonomous driving is formulated as a nonlinear o...An online trajectory planning method for collision avoidance is proposed to improve vehicle driving safety and comfort simultaneously.The collision-free trajectory for autonomous driving is formulated as a nonlinear optimization problem.A novel approximate convex optimization approach is developed for the online optimal trajectory in both longitudinal and lateral directions.First,a dual variable is used to model the non-convex collision-free constraint for driving safety and is calculated by solving a dual problem of the relative distance between vehicles.Second,the trajectory is further optimized in a model predictive control framework considering the safety.It realizes continuous-time and dynamic feasible motion with collision avoidance.The geometry of object vehicles is described by polygons instead of circles or ellipses in traditional methods.In order to avoid aggressive maneuver in the longitudinal and lateral directions for driving comfort,rates of the acceleration and the steering angle are restricted.The final formulated optimization problem is convex,which can be solved by using quadratic programming solvers and is computationally efficient for online application.Simulation results show that this approach can obtain similar driving performance compared to a state-of-the-art nonlinear optimization method.Furthermore,various driving scenarios are tested to evaluate the robustness and the ability for handling complex driving tasks.展开更多
Traditional research on automatic lane change has primarily focused on high-speed scenarios and has not considered the dynamic state changes of surrounding vehicles.This paper addresses this problem by proposing a tra...Traditional research on automatic lane change has primarily focused on high-speed scenarios and has not considered the dynamic state changes of surrounding vehicles.This paper addresses this problem by proposing a trajectory planning method to enable automatic lane change at medium and low speeds.The method is based on a dynamic safety domain model,which takes into account the actual state change of surrounding vehicles,as well as the upper boundary of the safety domain for collision avoidance and the lower boundary of comfort for vehicle stability.The proposed method involves the quantification of the safety and comfort boundaries through parametric modeling of the vehicle.A quintic polynomial trajectory planning method is proposed and evaluated through simulation and testing,resulting in improved safety and comfort for automatic lane change.展开更多
基金the National Natural Science Foundation of China(No.51965032)the National Natural Science Foundation of Gansu Province of China(No.22JR5RA319)+1 种基金the Excellent Dectoral Student Foundation of Gansu Province of China(No.23JRRA842)the Science and Technology Foundation of Gansu Province of China(No.21YF5WA060)。
文摘Given the unconstrained characteristics of the multi-robot coordinated towing system,the rope can only provide a unidirectional constraint force to the suspended object,which leads to the weak ability of the system to resist external disturbances and makes it difficult to control the trajectory of the suspended object.Based on the kinematics and statics of the multi-robot coordinated towing system with fixed base,the dynamic model of the system is established by using the Newton-Euler equations and the Udwadia-Kalaba equations.To plan the trajectories with high stability and strong control,trajectory planning is performed by combining the dynamics and stability of the towing system.Based on the dynamic stability of the motion trajectory of the suspended object,the stability of the suspended object is effectively improved through online real-time planning and offline manual adjustment.The effectiveness of the proposed method is verified by comparing the motion stability of the suspended object before and after planning.The results provide a foundation for the motion planning and coordinated control of the towing system.
基金supported by the National Key Research and Development Program of China(Grant 2020YFB1804800)the National Natural Science Foundation of China(Grant U22B2008 and Grant 61922010)the Beijing Natural Science Foundation(Grant JQ20019)。
文摘Unmanned aerial vehicles(UAVs)have attracted growing research interests in recent years,which can be used as cost-effective aerial platforms to transmit collected data packets to ground access points(APs).Thus,it is crucial to investigate robust airto-ground(A2G)wireless links for high-speed UAVs.However,the A2G wireless link is unstable as it suffers from large path-loss and severe Doppler effect due to the high mobility of UAVs.In order to meet these challenges,we propose an orthogonal time frequency space(OTFS)-based UAV communication system to relief the Doppler effect.Besides,considering that the energy of UAV is limited,we optimize the trajectory planning of UAV to minimize the energy consumption under the constraints of bit error rate(BER)and transmission rate,where the Doppler compensation is taken into account.Simulation results show that the performance of OTFS-based UAV system is superior to orthogonal frequency division multiplexing(OFDM)-based UAV systems,which can accomplish transmission tasks over shorter distances with lower energy consumption.
基金supported by the National Natural Science Foundation of China(11502019).
文摘To ensure safe flight of multiple fixed-wing unmanned aerial vehicles(UAVs)formation,considering trajectory planning and formation control together,a leader trajectory planning method based on the sparse A*algorithm is introduced.Firstly,a formation controller based on prescribed performance theory is designed to control the transient and steady formation configuration,as well as the formation forming time,which not only can form the designated formation configuration but also can guarantee collision avoidance and terrain avoidance theoretically.Next,considering the constraints caused by formation controller on trajectory planning such as the safe distance,turn angle and step length,as well as the constraint of formation shape,a leader trajectory planning method based on sparse A^(*)algorithm is proposed.Simulation results show that the UAV formation can arrive at the destination safely with a short trajectory no matter keeping the formation or encountering formation transformation.
基金Supported by National Natural Science Foundation of China(Grant Nos.52205014,51925502)the Fundamental Research Funds for the Central Universities(Grant Nos.JZ2022HGTA0325,JZ2022HGQA0147).
文摘Rehabilitation robots can help physiatrists to assist patients in improving their movement ability.Due to the interaction between rehabilitation robots and patients,the robots need to complete rehabilitation training on a safe basis.This paper presents an approach for smooth trajectory planning for a cable-driven parallel waist rehabilitation robot(CDPWRR)based on the rehabilitation evaluation factors.First,motion capture technology is used to collect the motion data of several volunteers in waist twisting.Considering the impact of motion variability,the feature points at the center of the human pelvis are obtained after eliminating unreasonable data through rationality judgments.Then,point-to-point waist training trajectory planning based on quintic polynomial and cycloid functions,and multipoint waist training trajectory planning based on quintic B-spline functions are carried out.The corresponding planned curves and kinematics characteristics using three methods are compared and analyzed.Subsequently,the rehabilitation evaluation factors are introduced to conduct smooth trajectory planning for waist training,and the waist trajectory with better compliance is obtained based on the safety and feasibility of waist motion.Finally,the physical prototype of the CDPWRR is built,and the feasibility and effectiveness of the proposed smooth trajectory planning method are proved by numerical analysis and experiments.
基金This work was supported by the Fundamental Research Funds for the Central Universities(No.2019XD-A07)the Director Fund of Beijing Key Laboratory of Space-ground Interconnection and Convergencethe National Key Laboratory of Science and Technology on Vacuum Electronics.
文摘The main aim of future mobile networks is to provide secure,reliable,intelligent,and seamless connectivity.It also enables mobile network operators to ensure their customer’s a better quality of service(QoS).Nowadays,Unmanned Aerial Vehicles(UAVs)are a significant part of the mobile network due to their continuously growing use in various applications.For better coverage,cost-effective,and seamless service connectivity and provisioning,UAVs have emerged as the best choice for telco operators.UAVs can be used as flying base stations,edge servers,and relay nodes in mobile networks.On the other side,Multi-access EdgeComputing(MEC)technology also emerged in the 5G network to provide a better quality of experience(QoE)to users with different QoS requirements.However,UAVs in a mobile network for coverage enhancement and better QoS face several challenges such as trajectory designing,path planning,optimization,QoS assurance,mobilitymanagement,etc.The efficient and proactive path planning and optimization in a highly dynamic environment containing buildings and obstacles are challenging.So,an automated Artificial Intelligence(AI)enabled QoSaware solution is needed for trajectory planning and optimization.Therefore,this work introduces a well-designed AI and MEC-enabled architecture for a UAVs-assisted future network.It has an efficient Deep Reinforcement Learning(DRL)algorithm for real-time and proactive trajectory planning and optimization.It also fulfills QoS-aware service provisioning.A greedypolicy approach is used to maximize the long-term reward for serving more users withQoS.Simulation results reveal the superiority of the proposed DRL mechanism for energy-efficient and QoS-aware trajectory planning over the existing models.
基金supported in part by the Project of International Cooperation and Exchanges NSFC under Grant No.61860206005in part by the Joint Funds of the NSFC under Grant No.U22A2003.
文摘In this paper,multi-UAV trajectory planning and resource allocation are jointly investigated to improve the information freshness for vehicular networks,where the vehicles collect time-critical traffic information by on-board sensors and upload to the UAVs through their allocated spectrum resource.We adopt the expected sum age of information(ESAoI)to measure the network-wide information freshness.ESAoI is jointly affected by both the UAVs trajectory and the resource allocation,which are coupled with each other and make the analysis of ESAoI challenging.To tackle this challenge,we introduce a joint trajectory planning and resource allocation procedure,where the UAVs firstly fly to their destinations and then hover to allocate resource blocks(RBs)during a time-slot.Based on this procedure,we formulate a trajectory planning and resource allocation problem for ESAoI minimization.To solve the mixed integer nonlinear programming(MINLP)problem with hybrid decision variables,we propose a TD3 trajectory planning and Round-robin resource allocation(TTPRRA).Specifically,we exploit the exploration and learning ability of the twin delayed deep deterministic policy gradient algorithm(TD3)for UAVs trajectory planning,and utilize Round Robin rule for the optimal resource allocation.With TTP-RRA,the UAVs obtain their flight velocities by sensing the locations and the age of information(AoI)of the vehicles,then allocate the RBs to the vehicles in a descending order of AoI until the remaining RBs are not sufficient to support another successful uploading.Simulation results demonstrate that TTP-RRA outperforms the baseline approaches in terms of ESAoI and average AoI(AAoI).
基金National Natural Science Foundation of China(Grant Nos.51925502,51575150).
文摘To avoid impacts and vibrations during the processes of acceleration and deceleration while possessing flexible working ways for cable-suspended parallel robots(CSPRs),point-to-point trajectory planning demands an under-constrained cable-suspended parallel robot(UCPR)with variable angle and height cable mast as described in this paper.The end-effector of the UCPR with three cables can achieve three translational degrees of freedom(DOFs).The inverse kinematic and dynamic modeling of the UCPR considering the angle and height of cable mast are completed.The motion trajectory of the end-effector comprising six segments is given.The connection points of the trajectory segments(except for point P3 in the X direction)are devised to have zero instantaneous velocities,which ensure that the acceleration has continuity and the planned acceleration curve achieves smooth transition.The trajectory is respectively planned using three algebraic methods,including fifth degree polynomial,cycloid trajectory,and double-S velocity curve.The results indicate that the trajectory planned by fifth degree polynomial method is much closer to the given trajectory of the end-effector.Numerical simulation and experiments are accomplished for the given trajectory based on fifth degree polynomial planning.At the points where the velocity suddenly changes,the length and tension variation curves of the planned and unplanned three cables are compared and analyzed.The OptiTrack motion capture system is adopted to track the end-effector of the UCPR during the experiment.The effectiveness and feasibility of fifth degree polynomial planning are validated.
基金supported by the National Natural Science Foundation of China(51605251)Tsinghua University Initiative Scientific Research Program(2014Z05093).
文摘A new seam-tracking method based on dynamic trajectory planning for a mobile welding robot is proposed in order to improve the response lag of the mobile robot and the high frequency oscillation in seam-tracking.By using a front-placed laser-based vision sensor to dynamically extract the location of the weld seam in front of torch,the trend and direction of the weld line is roughly obtained.The robot system autonomously and dynamically performs trajectory planning based on the isometric approximation model.Arc sensor technology is applied to detect the offset during welding process in real time.The dynamic compensation of the weld path is done in combination with the control of the mobile robot and the executive body installed on it.Simulated and experimental results demonstrate that the method effectively increases the stability of welding speed and smoothness of the weld track,and hence the weld formation in curves and corners is improved.
基金This work was supported by National Natural Science Foundation of China(NO.61703197 and NO.62061027).
文摘Unmanned Aerial Vehicles(UAVs)acting as aerial users to access the cellular network form a promising solution to guarantee its safe and efficient operations via the high-quality communication.Due to the flexible mobility of UAVs and the coverage range limits of ground base station(GBS),the signalto-noise ratio(SNR)of the communication link between UAVs and GBS will fluctuate.It is an important requirement to maintain the UAV’s cellular connection to meet a certain SNR requirement during the mission for UAV flying from take off to landing.In this paper,we study an efficient trajectory planning method that can minimize a cellular-connected UAV’s mission completion time under the connectivity requirement.The conventional method to tackle this problem adopts graph theory or a dynamic programming method to optimize the trajectory,which generally incurs high computational complexities.Moreover,there is a nonnegligible performance gap compared to the optimal solution.To this end,we propose an iterative trajectory optimizing algorithm based on geometric planning.Firstly,we apply graph theory to obtain all the possible UAV-GBS association sequences and select the candidate association sequences based on the topological relationship among UAV and GBSs.Next,adopting the triangle inequality property,an iterative handover location design is proposed to determine the shortest flight trajectory with fast convergence and low computation complexity.Then,the best flight trajectory can be obtained by comparing all the candidate trajectories.Lastly,we revealed the tradeoff between mission completion time and flight energy consumption.Numerical results validate that our proposed solution can obtain the effectiveness with set accuracy and outperform against the benchmark schemes with affordable computation time.
基金Supported by the Zhejiang Provincial Natural Science Foundation for Distinguished Young Scientists(Grant No.LR18E050003)the National Natural Science Foundation of China(Grant Nos.51975523,51905481)+2 种基金Natural Science Foundation of Zhejiang Province(Grant No.LY22E050012)the Students in Zhejiang Province Science and Technology Innovation Plan(Xinmiao Talents Program)(Grant No.2020R403054)the China Postdoctoral Science Foundation(Grant No.2020M671784)。
文摘Robot manipulators perform a point-point task under kinematic and dynamic constraints.Due to multi-degreeof-freedom coupling characteristics,it is difficult to find a better desired trajectory.In this paper,a multi-objective trajectory planning approach based on an improved elitist non-dominated sorting genetic algorithm(INSGA-II)is proposed.Trajectory function is planned with a new composite polynomial that by combining of quintic polynomials with cubic Bezier curves.Then,an INSGA-II,by introducing three genetic operators:ranking group selection(RGS),direction-based crossover(DBX)and adaptive precision-controllable mutation(APCM),is developed to optimize travelling time and torque fluctuation.Inverted generational distance,hypervolume and optimizer overhead are selected to evaluate the convergence,diversity and computational effort of algorithms.The optimal solution is determined via fuzzy comprehensive evaluation to obtain the optimal trajectory.Taking a serial-parallel hybrid manipulator as instance,the velocity and acceleration profiles obtained using this composite polynomial are compared with those obtained using a quintic B-spline method.The effectiveness and practicability of the proposed method are verified by simulation results.This research proposes a trajectory optimization method which can offer a better solution with efficiency and stability for a point-to-point task of robot manipulators.
文摘Aiming at the yaw problem caused by inertial navigation system errors accumulation during the navigation of an intelligent aircraft,a three-dimensional trajectory planning method based on the particle swarm optimization-A star(PSO-A*)algorithm is designed.Firstly,an environment model for aircraft error correction is established,and the trajectory is discretized to calculate the positioning error.Next,the positioning error is corrected at many preset trajectory points.The shortest trajectory and the fewest correction times are regarded as optimization goals to improve the heuristic function of A star(A*)algorithm.Finally,the index weights are continuously optimized by the particle swarm optimization algorithm.The optimal trajectory is found by the A*algorithm under the current evaluation index,so the ideal trajectory is planned.The experimental results show that the PSO-A*algorithm can quickly search for ideal trajectories in different environment models,indicating that the algorithm has certain feasibility and adaptability,and verifies the rationality of the proposed trajectory planning model.The PSO-A*algorithm has better convergence accuracy than the A*algorithm,and the search efficiency is significantly better than the grid search A star(GS-A*)algorithm.The PSO-A*algorithm proposed in this paper has certain engineering application value.The researchers will study the real-time and systematic nature of the algorithm.
基金Supported by National Key R&D Program of China(Grant No.2019YFB1311404)。
文摘To accommodate the gait and balance disorder of the elderly with age progression and the occurrence of various senile diseases,this paper proposes a novel gait balance training robot(G-Balance)based on a six degree-of-freedom parallel platform.Using the platform movement and IMU wearable sensors,two training modes,i.e.,active and passive,are developed to achieve vestibular stimulation.Virtual reality technology is applied to achieve visual stimulation.In the active training mode,the elderly actively exercises to control the posture change of the platform and the switching of the virtual scene.In the passive training mode,the platform movement is combined with the virtual scene to simulate bumpy environments,such as earthquakes,to enhance the human anti-interference ability.To achieve a smooth switching of the scene,continuous speed and acceleration of the platform motion are required in some scenarios,in which a trajectory planning algorithm is applied.This paper describes the application of the trajectory planning algorithm in the balance training mode and the optimization of jerk(differential of acceleration)based on cubic spline planning,which can reduce impact on the joint and enhance stability.
基金National Natural Science Foundation of China(Grant Nos.51922057,91948301).
文摘High-speed parallel robots have been extensively utilized in the light industry.However,the influence of the nonlinear dynamic characteristics of high-speed parallel robots on system’s dynamic response and stable operation cannot be ignored during the high-speed reciprocating motion.Thus,trajectory planning is essential for efficiency and stability from pick-and-place(PAP)actions.This paper presents a method for planning the equal-height pick-and-place trajectory considering velocity constraints to improve the PAP efficiency and stability of high-speed parallel robots.The velocity constraints in the start-and-end points can reduce vibration from picking and placing,making the trajectory more suitable to complex beltline situations.Based on velocity constraints,trajectory optimization includes trajectory smoothness and joint torque to optimize cycle time is carried out.This paper proposes an online trajectory optimization solution.By using back propagation(BP)neural networks,the solution is simplified and can be solved in real-time.Simulation and experiments were carried out on the SR4 parallel robot.The results show that the proposed method improves the efficiency,smoothness,and stability of the robot.This paper proposes an online trajectory planning method which is velocity constraints based and can improve the efficiency and stability of high-speed parallel robots.The work of this research is conducive to finely applying high-speed parallel robots.
基金supported in part by the Research Grants Council of the Hong Kong Special Administrative Region of China(11202318,11203721)the Australian Research Council(DP200100700)。
文摘This paper addresses a major issue in planning the trajectories of under-actuated autonomous vehicles based on neurodynamic optimization.A receding-horizon vehicle trajectory planning task is formulated as a sequential global optimization problem with weighted quadratic navigation functions and obstacle avoidance constraints based on given vehicle goal configurations.The feasibility of the formulated optimization problem is guaranteed under derived conditions.The optimization problem is sequentially solved via collaborative neurodynamic optimization in a neurodynamics-driven trajectory planning method/procedure.Simulation results with under-actuated unmanned wheeled vehicles and autonomous surface vehicles are elaborated to substantiate the efficacy of the neurodynamics-driven trajectory planning method.
文摘In this paper,a fast approach to generate time optimal and smooth trajectory has been developed and tested.Minimum time is critical for the productivity in industrial applications.Meanwhile,smooth trajectories based on cubic splines are desirable for their ability to limit vibrations and ensure the continuity of position,velocity and acceleration during the robot movement.The main feature of the approach is a satisfactory solution that can be obtained by a local modification process among each interval between two consecutive via-points.An analytical formulation simplifies the approach to smooth trajectory and few iterations are enough to determine the correct values.The approach can be applied in many robot manipulators which require high performance on time and smooth.The simulation and application of the approach on a palletizer robot are performed,and the experimental results provide evidence that the approach can realize the robot manipulators more efficiency and high smooth performance.
基金Fund of Taishan Scholar in Shandong Province,Shandong University of Science and Technology Research Fund(No.2010KYTD101)
文摘This paper investiga tes a trajectory planning algorithm to reduce the manipulator’s working time.A t ime-optimal trajectory planning(TOTP)is conducted based on improved ad aptive genetic algorithm(IAGA)and combined with cubic triangular Bezier spline(CTBS).The CTBS based trajectory planning we did before can achieve continuous second and third derivation,hence it meets the stability requirements of the m anipulator.The working time can be greatly reduced by applying IAGA to the puma 560 trajectory planning when considering physical constraints such as angular ve locity,angular acceleration and jerk.Simulation experiments in both Matlab and ADAMS illustrate that TOTP based on IAGA can give a time optimal result with sm oothness and stability.
基金supported by the National Key Research and Development Program of China(2019YFB1707505)the National Natural Science Foundation of China(Grant No.52005436)。
文摘The trend towards automation and intelligence in aircraft final assembly testing has led to a new demand for autonomous perception of unknown cockpit operation scenes in robotic collaborative airborne system testing.To address this demand,a robotic automated 3D reconstruction cell which enables to autonomously plan the robot end-camera’s trajectory is developed for image acquisition and 3D modeling of the cockpit operation scene.A continuous viewpoint path planning algorithm is proposed that incorporates both 3D reconstruction quality and robot path quality into optimization process.Smoothness metrics for viewpoint position paths and orientation paths are introduced together for the first time in 3D reconstruction.To ensure safe and effective movement,two spatial constraints,Domain of View Admissible Position(DVAP)and Domain of View Admissible Orientation(DVAO),are implemented to account for robot reachability and collision avoidance.By using diffeomorphism mapping,the orientation path is transformed into 3D,consistent with the position path.Both orientation and position paths can be optimized in a unified framework to maximize the gain of reconstruction quality and path smoothness within DVAP and DVAO.The reconstruction cell is capable of automatic data acquisition and fine scene modeling,using the generated robot C-space trajectory.Simulation and physical scene experiments have confirmed the effectiveness of the proposed method to achieve highprecision 3D reconstruction while optimizing robot motion quality.
基金supported by the National Natural Science Foundation of China(Grant Nos.62225305,12072088,62003117,and 62003118)the National Defense Basic Scientific Research Program of China(Grant No.JCKY2020603B010)+1 种基金the Lab of Space Optoelectronic Measurement&Perception(Grant No.LabSOMP-2021-06)the Natural Science Foundation of Heilongjiang Province,China(Grant No.ZD2020F001)。
文摘This paper is concerned with trajectory planning problems for UAVs operating near ground.Most existing studies focus on solving the problem of collision-free trajectory planning between pre-defined path points,but ignore the need of navigation method for UAVs working on specific operating surfaces in near-ground space.In this paper,a novel near-ground trajectory planning framework is proposed,where the hybrid voxel-surfel map is developed to model the environment with special attention to the uneven operating surface.To improve the frequency of updates,a probability-based surfel fusion method and a resolution adaptive adjustment method based on the fusion result are proposed in this paper.By using possibility information in the map,a path search method is established to generate the initial trajectory.The trajectory is then further optimized based on map gradient information to generate a final trajectory that tracks the specified operating surface according to the task requirements.Compared with existing methods,the multi-resolution hybrid voxel-surfel map proposed in this paper has advantages in terms of operating efficiency.A series of experiments in simulated and real scenarios validate the effectiveness of the proposed trajectory planning framework.
基金supported by Natural Science Foundation of Beijing(Grant No.3212013)Young Elite Scientists Sponsorship Program by CAST and Beijing JinQiao Project.
文摘An online trajectory planning method for collision avoidance is proposed to improve vehicle driving safety and comfort simultaneously.The collision-free trajectory for autonomous driving is formulated as a nonlinear optimization problem.A novel approximate convex optimization approach is developed for the online optimal trajectory in both longitudinal and lateral directions.First,a dual variable is used to model the non-convex collision-free constraint for driving safety and is calculated by solving a dual problem of the relative distance between vehicles.Second,the trajectory is further optimized in a model predictive control framework considering the safety.It realizes continuous-time and dynamic feasible motion with collision avoidance.The geometry of object vehicles is described by polygons instead of circles or ellipses in traditional methods.In order to avoid aggressive maneuver in the longitudinal and lateral directions for driving comfort,rates of the acceleration and the steering angle are restricted.The final formulated optimization problem is convex,which can be solved by using quadratic programming solvers and is computationally efficient for online application.Simulation results show that this approach can obtain similar driving performance compared to a state-of-the-art nonlinear optimization method.Furthermore,various driving scenarios are tested to evaluate the robustness and the ability for handling complex driving tasks.
文摘Traditional research on automatic lane change has primarily focused on high-speed scenarios and has not considered the dynamic state changes of surrounding vehicles.This paper addresses this problem by proposing a trajectory planning method to enable automatic lane change at medium and low speeds.The method is based on a dynamic safety domain model,which takes into account the actual state change of surrounding vehicles,as well as the upper boundary of the safety domain for collision avoidance and the lower boundary of comfort for vehicle stability.The proposed method involves the quantification of the safety and comfort boundaries through parametric modeling of the vehicle.A quintic polynomial trajectory planning method is proposed and evaluated through simulation and testing,resulting in improved safety and comfort for automatic lane change.
