Automatic control technology is the basis of road robot improvement,according to the characteristics of construction equipment and functions,the research will be input type perception from positioning acquisition,real...Automatic control technology is the basis of road robot improvement,according to the characteristics of construction equipment and functions,the research will be input type perception from positioning acquisition,real-world monitoring,the process will use RTK-GNSS positional perception technology,by projecting the left side of the earth from Gauss-Krueger projection method,and then carry out the Cartesian conversion based on the characteristics of drawing;steering control system is the core of the electric drive unmanned module,on the basis of the analysis of the composition of the steering system of unmanned engineering vehicles,the steering system key components such as direction,torque sensor,drive motor and other models are established,the joint simulation model of unmanned engineering vehicles is established,the steering controller is designed using the PID method,the simulation results show that the control method can meet the construction path demand for automatic steering.The path planning will first formulate the construction area with preset values and realize the steering angle correction during driving by PID algorithm,and never realize the construction-based path planning,and the results show that the method can control the straight path within the error of 10 cm and the curve error within 20 cm.With the collaboration of various modules,the automatic construction simulation results of this robot show that the design path and control method is effective.展开更多
An increase in car ownership brings convenience to people’s life.However,it also leads to frequent traffic accidents.Precisely forecasting surrounding agents’future trajectories could effectively decrease vehicle-ve...An increase in car ownership brings convenience to people’s life.However,it also leads to frequent traffic accidents.Precisely forecasting surrounding agents’future trajectories could effectively decrease vehicle-vehicle and vehicle-pedestrian collisions.Long-short-term memory(LSTM)network is often used for vehicle trajectory prediction,but it has some shortages such as gradient explosion and low efficiency.A trajectory prediction method based on an improved Transformer network is proposed to forecast agents’future trajectories in a complex traffic environment.It realizes the transformation from sequential step processing of LSTM to parallel processing of Transformer based on attentionmechanism.To performtrajectory predictionmore efficiently,a probabilistic sparse self-attention mechanism is introduced to reduce attention complexity by reducing the number of queried values in the attention mechanism.Activate or not(ACON)activation function is adopted to select whether to activate or not,hence improving model flexibility.The proposed method is evaluated on the publicly available benchmarks nextgeneration simulation(NGSIM)and ETH/UCY.The experimental results indicate that the proposed method can accurately and efficiently predict agents’trajectories.展开更多
Parkinson’s disease(PD)is a very common neurodegenerative disease that occurs mostly in the elderly.There are many main clinical manifestations of PD,such as tremor,bradykinesia,muscle rigidity,etc.Based on the curre...Parkinson’s disease(PD)is a very common neurodegenerative disease that occurs mostly in the elderly.There are many main clinical manifestations of PD,such as tremor,bradykinesia,muscle rigidity,etc.Based on the current research on PD,the accurate and convenient detection of early symptoms is the key to detect PD.With the development of microelectronic and sensor technology,it is much easier to measure the barely noticeable tremor in just one hand for the early detection of Parkinson’s disease.In this paper,we present a smart wearable device for detecting hand tremor,in which MPU6050(MIDI Processing Unit)consisting of a 3-axis gyroscope and a 3-axis accelerometer is used to collect acceleration and angular velocity of fingers.By analyzing the time of specific finger movements,we successfully recognized the tremor signals with high accuracy.Meanwhile,with Bluetooth 4.0(Bluetooth Low Energy,BLE)and networking terminal ability,tremor data can be transferred to a monitoring device in real time with extremely lowenergy consumption.The experimental results have shown that the proposed device(smart ring)is convenient for long-term tremor detection which is vital for early detection and treatment for Parkinson’s disease.展开更多
It is different for the liquid tank semi-trailer to keep roll stability during turning or emergency voidance,and that may cause serious accidents.Although the scholars did lots of research about the roll stability of ...It is different for the liquid tank semi-trailer to keep roll stability during turning or emergency voidance,and that may cause serious accidents.Although the scholars did lots of research about the roll stability of liquid tank semi-trailer in theory by calculating and simulation,how to make an effective early warning of rollover is still unsolved in practice.The reasons include the complex driving condition and the difficulty of the vehicle parameter obtaining.The feasible method used currently is evaluating the roll stability of a liquid tank semi-trailer by the lateral acceleration or the attitude of the vehicle.Unfortunately,the lateral acceleration is more useful for sideslip rather than rollover,and the attitude is a kind of posterior way,which means it is hard to take measures to cope with the rollover accident when the attitude exceeds the safety threshold.Considering the movement of the vehicle is totally caused by the wheel force,the rollover could also be predicted by the changing of the wheel force.Therefore,in this paper,we developed a method to analyze the roll stability by the vertical wheel force.A thorough experiment environment is established,and the effectiveness of the proposed method is verified in real driving conditions.展开更多
文摘Automatic control technology is the basis of road robot improvement,according to the characteristics of construction equipment and functions,the research will be input type perception from positioning acquisition,real-world monitoring,the process will use RTK-GNSS positional perception technology,by projecting the left side of the earth from Gauss-Krueger projection method,and then carry out the Cartesian conversion based on the characteristics of drawing;steering control system is the core of the electric drive unmanned module,on the basis of the analysis of the composition of the steering system of unmanned engineering vehicles,the steering system key components such as direction,torque sensor,drive motor and other models are established,the joint simulation model of unmanned engineering vehicles is established,the steering controller is designed using the PID method,the simulation results show that the control method can meet the construction path demand for automatic steering.The path planning will first formulate the construction area with preset values and realize the steering angle correction during driving by PID algorithm,and never realize the construction-based path planning,and the results show that the method can control the straight path within the error of 10 cm and the curve error within 20 cm.With the collaboration of various modules,the automatic construction simulation results of this robot show that the design path and control method is effective.
基金the SuzhouKey industrial technology innovation project SYG202031the Future Network Scientific Research Fund Project,FNSRFP-2021-YB-29.
文摘An increase in car ownership brings convenience to people’s life.However,it also leads to frequent traffic accidents.Precisely forecasting surrounding agents’future trajectories could effectively decrease vehicle-vehicle and vehicle-pedestrian collisions.Long-short-term memory(LSTM)network is often used for vehicle trajectory prediction,but it has some shortages such as gradient explosion and low efficiency.A trajectory prediction method based on an improved Transformer network is proposed to forecast agents’future trajectories in a complex traffic environment.It realizes the transformation from sequential step processing of LSTM to parallel processing of Transformer based on attentionmechanism.To performtrajectory predictionmore efficiently,a probabilistic sparse self-attention mechanism is introduced to reduce attention complexity by reducing the number of queried values in the attention mechanism.Activate or not(ACON)activation function is adopted to select whether to activate or not,hence improving model flexibility.The proposed method is evaluated on the publicly available benchmarks nextgeneration simulation(NGSIM)and ETH/UCY.The experimental results indicate that the proposed method can accurately and efficiently predict agents’trajectories.
基金supported by the National Natural Science Foundation of China(Grant Nos.61972207 and 61802196)Jiangsu Provincial Government Scholarship for Studying Abroad and the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)fund.
文摘Parkinson’s disease(PD)is a very common neurodegenerative disease that occurs mostly in the elderly.There are many main clinical manifestations of PD,such as tremor,bradykinesia,muscle rigidity,etc.Based on the current research on PD,the accurate and convenient detection of early symptoms is the key to detect PD.With the development of microelectronic and sensor technology,it is much easier to measure the barely noticeable tremor in just one hand for the early detection of Parkinson’s disease.In this paper,we present a smart wearable device for detecting hand tremor,in which MPU6050(MIDI Processing Unit)consisting of a 3-axis gyroscope and a 3-axis accelerometer is used to collect acceleration and angular velocity of fingers.By analyzing the time of specific finger movements,we successfully recognized the tremor signals with high accuracy.Meanwhile,with Bluetooth 4.0(Bluetooth Low Energy,BLE)and networking terminal ability,tremor data can be transferred to a monitoring device in real time with extremely lowenergy consumption.The experimental results have shown that the proposed device(smart ring)is convenient for long-term tremor detection which is vital for early detection and treatment for Parkinson’s disease.
基金This work was supported by the Suzhou Key industrial technology innovation project SYG202031.
文摘It is different for the liquid tank semi-trailer to keep roll stability during turning or emergency voidance,and that may cause serious accidents.Although the scholars did lots of research about the roll stability of liquid tank semi-trailer in theory by calculating and simulation,how to make an effective early warning of rollover is still unsolved in practice.The reasons include the complex driving condition and the difficulty of the vehicle parameter obtaining.The feasible method used currently is evaluating the roll stability of a liquid tank semi-trailer by the lateral acceleration or the attitude of the vehicle.Unfortunately,the lateral acceleration is more useful for sideslip rather than rollover,and the attitude is a kind of posterior way,which means it is hard to take measures to cope with the rollover accident when the attitude exceeds the safety threshold.Considering the movement of the vehicle is totally caused by the wheel force,the rollover could also be predicted by the changing of the wheel force.Therefore,in this paper,we developed a method to analyze the roll stability by the vertical wheel force.A thorough experiment environment is established,and the effectiveness of the proposed method is verified in real driving conditions.
