The forward design of trajectory planning strategies requires preset trajectory optimization functions,resulting in poor adaptability of the strategy and an inability to accurately generate obstacle avoidance trajecto...The forward design of trajectory planning strategies requires preset trajectory optimization functions,resulting in poor adaptability of the strategy and an inability to accurately generate obstacle avoidance trajectories that conform to real driver behavior habits.In addition,owing to the strong time-varying dynamic characteristics of obstacle avoidance scenarios,it is necessary to design numerous trajectory optimization functions and adjust the corresponding parameters.Therefore,an anthropomorphic obstacle-avoidance trajectory planning strategy for adaptive driving scenarios is proposed.First,numerous expert-demonstrated trajectories are extracted from the HighD natural driving dataset.Subsequently,a trajectory expectation feature-matching algorithm is proposed that uses maximum entropy inverse reinforcement learning theory to learn the extracted expert-demonstrated trajectories and achieve automatic acquisition of the optimization function of the expert-demonstrated trajectory.Furthermore,a mapping model is constructed by combining the key driving scenario information that affects vehicle obstacle avoidance with the weight of the optimization function,and an anthropomorphic obstacle avoidance trajectory planning strategy for adaptive driving scenarios is proposed.Finally,the proposed strategy is verified based on real driving scenarios.The results show that the strategy can adjust the weight distribution of the trajectory optimization function in real time according to the“emergency degree”of obstacle avoidance and the state of the vehicle.Moreover,this strategy can generate anthropomorphic trajectories that are similar to expert-demonstrated trajectories,effectively improving the adaptability and acceptability of trajectories in driving scenarios.展开更多
Each joint of a hydraulic-driven legged robot adopts a highly integrated hydraulic drive unit(HDU),which features a high power-weight ratio.However,most HDUs are throttling-valve-controlled cylinder systems,which exhi...Each joint of a hydraulic-driven legged robot adopts a highly integrated hydraulic drive unit(HDU),which features a high power-weight ratio.However,most HDUs are throttling-valve-controlled cylinder systems,which exhibit high energy losses.By contrast,pump control systems offer a high efficiency.Nevertheless,their response ability is unsatisfactory.To fully utilize the advantages of pump and valve control systems,in this study,a new type of pump-valve compound drive system(PCDS)is designed,which can not only effectively reduce the energy loss,but can also ensure the response speed and response accuracy of the HDUs in robot joints to satisfy the performance requirements of robots.Herein,considering the force control requirements of energy conservation,high precision,and fast response of the robot joint HDU,a nonlinear mathematical model of the PCDS force control system is first introduced.In addition,pressure-flow nonlinearity,friction nonlinearity,load complexity and variability,and other factors affecting the system are considered,and a novel force control method based on quantitative feedback theory(QFT)and a disturbance torque observer(DTO)is designed,which is denoted as QFT-DTOC herein.This method improves the control accuracy and robustness of the force control system,reduces the effect of the disturbance torque on the control performance of the servo motor,and improves the overall force control performance of the system.Finally,experimental verification is performed using the PCDS performance test platform.The experimental results and quantitative data show that the QFT-DTOC proposed herein can significantly improve the force control performance of the PCDS.The relevant force control method can be used as a bottom-control method for the hydraulic servo system to provide a foundation for implementing the top-level trajectory planning of the robot.展开更多
The genetic based Dual Instinct Theory is determined by evolutionary history. Aggression is required for survival and sex for propagation of species. Aggressive and sexual drive derivatives with their corresponding de...The genetic based Dual Instinct Theory is determined by evolutionary history. Aggression is required for survival and sex for propagation of species. Aggressive and sexual drive derivatives with their corresponding defence mechanisms are combined with biologically based stages of infant/child development and the functional entity of Structural Theory. This model of human nature is the applied to the diagnostic categories of DSM-5-TR. Objectives: To follow the innate Dual Instinct Theory from life to death and through Artificial Intelligence;connect it with biological stages of development of the Structural Theory and illustrate its manifestations in DSM-5-TR classifications. Method: Review of selected published literature. Applying the principle of focus and cognition of informed clinical observation of innate drive derivatives in conjunction with The Structural Theory. Both theories are functional entities with no structures involved. Sigmund Freud’s biologically based stages of development;oral, anal, genital pubic, adult, and geriatric along with a variety of unconscious, automatic, and persistent defense mechanisms are selectively folded into diagnosis listed in the manual.展开更多
The introduction of automated driving systems raised questions about how the human driver interacts with the automated system. Non-cooperative game theory is increasingly used for modelling and understanding such inte...The introduction of automated driving systems raised questions about how the human driver interacts with the automated system. Non-cooperative game theory is increasingly used for modelling and understanding such interaction, while its counterpart, cooperative game theory is rarely discussed for similar applications despite it may be potentially more suitable. This paper describes the modelling of a human driver’s steering interaction with an automated steering system using cooperative game theory. The distributed Model Predictive Control approach is adopted to derive the driver’s and the automated steering system’s strategies in a Pareto equilibrium sense, namely their cooperative Pareto steering strategies. Two separate numerical studies are carried out to study the influence of strategy parameters, and the influence of strategy types on the driver’s and the automated system’s steering performance. It is found that when a driver interacts with an automated steering system using a cooperative Pareto steering strategy, the driver can improve his/her performance in following a target path through increasing his/her effort in pursuing his/her own interest under the driver-automation cooperative control goal. It is also found that a driver’s adoption of cooperative Pareto steering strategy leads to a reinforcement in the driver’s steering angle control, compared to the driver’s adoption of non-cooperative Nash strategy. This in turn enables the vehicle to return from a lane-change maneuver to straight-line driving swifter.展开更多
By rigidizing the input joints, all possible combinations of drive selecting for the 4-PPPS parallel mechanism are analyzed based on the screw theory in this paper, and the five of them are proved to be reasonable. Th...By rigidizing the input joints, all possible combinations of drive selecting for the 4-PPPS parallel mechanism are analyzed based on the screw theory in this paper, and the five of them are proved to be reasonable. Then choosing the one as mechanical actuators, the workspace of the 4-PPPS parallel mechanism is deduced according to the rational input scheme. Finally the rationality of input scheme for this mechanism is identified on the basis of the continuity of the workspace.展开更多
The characteristics of novel cone-generated cylindrical worm and the machining princi- ple of using a grinding wheel with two degree-of-freedom motions are described. A systematic study is made on the first enveloping...The characteristics of novel cone-generated cylindrical worm and the machining princi- ple of using a grinding wheel with two degree-of-freedom motions are described. A systematic study is made on the first enveloping process of the grinding wheel forming a worm and the second enveloping process of the worm forming a worm wheel with the meshing theory of kinematic method. Some numerical calculation formulas and important conclusions are obtained.展开更多
基金supported by the National Natural Science Foundation of China(51875302)。
文摘The forward design of trajectory planning strategies requires preset trajectory optimization functions,resulting in poor adaptability of the strategy and an inability to accurately generate obstacle avoidance trajectories that conform to real driver behavior habits.In addition,owing to the strong time-varying dynamic characteristics of obstacle avoidance scenarios,it is necessary to design numerous trajectory optimization functions and adjust the corresponding parameters.Therefore,an anthropomorphic obstacle-avoidance trajectory planning strategy for adaptive driving scenarios is proposed.First,numerous expert-demonstrated trajectories are extracted from the HighD natural driving dataset.Subsequently,a trajectory expectation feature-matching algorithm is proposed that uses maximum entropy inverse reinforcement learning theory to learn the extracted expert-demonstrated trajectories and achieve automatic acquisition of the optimization function of the expert-demonstrated trajectory.Furthermore,a mapping model is constructed by combining the key driving scenario information that affects vehicle obstacle avoidance with the weight of the optimization function,and an anthropomorphic obstacle avoidance trajectory planning strategy for adaptive driving scenarios is proposed.Finally,the proposed strategy is verified based on real driving scenarios.The results show that the strategy can adjust the weight distribution of the trajectory optimization function in real time according to the“emergency degree”of obstacle avoidance and the state of the vehicle.Moreover,this strategy can generate anthropomorphic trajectories that are similar to expert-demonstrated trajectories,effectively improving the adaptability and acceptability of trajectories in driving scenarios.
基金Supported by National Excellent Natural Science Foundation of China(Grant No.52122503)Hebei Provincial Natural Science Foundation of China(Grant No.E2022203002)+2 种基金The Yanzhao’s Young Scientist Project of China(Grant No.E2023203258)Science Research Project of Hebei Education Department of China(Grant No.BJK2022060)Hebei Provincial Graduate Innovation Funding Project of China(Grant No.CXZZSS2022129).
文摘Each joint of a hydraulic-driven legged robot adopts a highly integrated hydraulic drive unit(HDU),which features a high power-weight ratio.However,most HDUs are throttling-valve-controlled cylinder systems,which exhibit high energy losses.By contrast,pump control systems offer a high efficiency.Nevertheless,their response ability is unsatisfactory.To fully utilize the advantages of pump and valve control systems,in this study,a new type of pump-valve compound drive system(PCDS)is designed,which can not only effectively reduce the energy loss,but can also ensure the response speed and response accuracy of the HDUs in robot joints to satisfy the performance requirements of robots.Herein,considering the force control requirements of energy conservation,high precision,and fast response of the robot joint HDU,a nonlinear mathematical model of the PCDS force control system is first introduced.In addition,pressure-flow nonlinearity,friction nonlinearity,load complexity and variability,and other factors affecting the system are considered,and a novel force control method based on quantitative feedback theory(QFT)and a disturbance torque observer(DTO)is designed,which is denoted as QFT-DTOC herein.This method improves the control accuracy and robustness of the force control system,reduces the effect of the disturbance torque on the control performance of the servo motor,and improves the overall force control performance of the system.Finally,experimental verification is performed using the PCDS performance test platform.The experimental results and quantitative data show that the QFT-DTOC proposed herein can significantly improve the force control performance of the PCDS.The relevant force control method can be used as a bottom-control method for the hydraulic servo system to provide a foundation for implementing the top-level trajectory planning of the robot.
文摘The genetic based Dual Instinct Theory is determined by evolutionary history. Aggression is required for survival and sex for propagation of species. Aggressive and sexual drive derivatives with their corresponding defence mechanisms are combined with biologically based stages of infant/child development and the functional entity of Structural Theory. This model of human nature is the applied to the diagnostic categories of DSM-5-TR. Objectives: To follow the innate Dual Instinct Theory from life to death and through Artificial Intelligence;connect it with biological stages of development of the Structural Theory and illustrate its manifestations in DSM-5-TR classifications. Method: Review of selected published literature. Applying the principle of focus and cognition of informed clinical observation of innate drive derivatives in conjunction with The Structural Theory. Both theories are functional entities with no structures involved. Sigmund Freud’s biologically based stages of development;oral, anal, genital pubic, adult, and geriatric along with a variety of unconscious, automatic, and persistent defense mechanisms are selectively folded into diagnosis listed in the manual.
文摘The introduction of automated driving systems raised questions about how the human driver interacts with the automated system. Non-cooperative game theory is increasingly used for modelling and understanding such interaction, while its counterpart, cooperative game theory is rarely discussed for similar applications despite it may be potentially more suitable. This paper describes the modelling of a human driver’s steering interaction with an automated steering system using cooperative game theory. The distributed Model Predictive Control approach is adopted to derive the driver’s and the automated steering system’s strategies in a Pareto equilibrium sense, namely their cooperative Pareto steering strategies. Two separate numerical studies are carried out to study the influence of strategy parameters, and the influence of strategy types on the driver’s and the automated system’s steering performance. It is found that when a driver interacts with an automated steering system using a cooperative Pareto steering strategy, the driver can improve his/her performance in following a target path through increasing his/her effort in pursuing his/her own interest under the driver-automation cooperative control goal. It is also found that a driver’s adoption of cooperative Pareto steering strategy leads to a reinforcement in the driver’s steering angle control, compared to the driver’s adoption of non-cooperative Nash strategy. This in turn enables the vehicle to return from a lane-change maneuver to straight-line driving swifter.
文摘By rigidizing the input joints, all possible combinations of drive selecting for the 4-PPPS parallel mechanism are analyzed based on the screw theory in this paper, and the five of them are proved to be reasonable. Then choosing the one as mechanical actuators, the workspace of the 4-PPPS parallel mechanism is deduced according to the rational input scheme. Finally the rationality of input scheme for this mechanism is identified on the basis of the continuity of the workspace.
文摘The characteristics of novel cone-generated cylindrical worm and the machining princi- ple of using a grinding wheel with two degree-of-freedom motions are described. A systematic study is made on the first enveloping process of the grinding wheel forming a worm and the second enveloping process of the worm forming a worm wheel with the meshing theory of kinematic method. Some numerical calculation formulas and important conclusions are obtained.
