In this study,a walking method that prevents a fall of the planetary exploration-legged rover is proposed.In the proposed walking method,the leg is sunk by giving vibration to the ground.The posture of the rover is ch...In this study,a walking method that prevents a fall of the planetary exploration-legged rover is proposed.In the proposed walking method,the leg is sunk by giving vibration to the ground.The posture of the rover is changed to prevent a fall of the rover by sinking the leg.First,the relationship between the kind of vibration and the subsidence of the leg is confirmed.In this experimental result,the leg is shown to be easy to sink to the ground by giving vibration.Moreover,the larger the vibratory force is,the easier the leg sinks to the ground.Finally,the legged testbed walks on the loose ground with a slope using the proposed walking method.In this experimental result,the testbed is difficult to fall down when it uses the proposed walking.Moreover,the angle of a slope that the testbed can walk becomes large by using the proposed walking.展开更多
Inertial navigation system/visual navigation system(INS/VNS) integrated navigation is a commonly used autonomous navigation method for planetary rovers. Since visual measurements are related to the previous and curren...Inertial navigation system/visual navigation system(INS/VNS) integrated navigation is a commonly used autonomous navigation method for planetary rovers. Since visual measurements are related to the previous and current state vectors(position and attitude) of planetary rovers, the performance of the Kalman filter(KF) will be challenged by the time-correlation problem. A state augmentation method, which augments the previous state value to the state vector, is commonly used when dealing with this problem. However, the augmenting of state dimensions will result in an increase in computation load. In this paper, a state dimension reduced INS/VNS integrated navigation method based on coordinates of feature points is presented that utilizes the information obtained through INS/VNS integrated navigation at a previous moment to overcome the time relevance problem and reduce the dimensions of the state vector. Equations of extended Kalman filter(EKF) are used to demonstrate the equivalence of calculated results between the proposed method and traditional state augmented methods. Results of simulation and experimentation indicate that this method has less computational load but similar accuracy when compared with traditional methods.展开更多
In order to ensure the safety and efficiency of planetary exploration rovers,path planning and tracking control of a planetary rover are expected to consider factors such as complex 3D terrain features,the motion cons...In order to ensure the safety and efficiency of planetary exploration rovers,path planning and tracking control of a planetary rover are expected to consider factors such as complex 3D terrain features,the motion constraints of the rover,traversability,etc.An improved path planning and tracking control method is proposed for planetary exploration rovers on rough terrain in this paper.Firstly,the kinematic model of the planetary rover is established.A 3D motion primitives library adapted to various terrains and the rover’s orientations is generated.The state expansion process and heuristic function of the A*algorithm are improved using the motion primitives and terrain features.Global path is generated by improved A*-based algorithm that satisfies the planetary rover’s kinematic constraints and the 3D terrain restrictions.Subsequently,an optional arc path set is designed based on the traversable capabilities of the planetary rover.Each arc path corresponds to a specific motion that determines the linear and angular velocities of the planetary rover.The optimal path is selected through the multi-objective evaluation function.The planetary rover is driven to accurately track the global path by sending optimal commands that corresponds to the optimal path for real-time obstacle avoidance.Finally,the path planning and tracking control method is effectively validated during a given mission through two simulation tests.The experiment results show that the improved A*-based algorithm reduces planning time by 30.05% and generates smoother paths than the classic A^(*) algorithm.The multi-objective arc-based method improves the rover’s motion efficiency,ensuring safer and quicker mission completion along the global path.展开更多
In this paper, the TAS-I （Thales Alenia Space-Italy） Test Bench for Robotics and Autonomy （TBRA） is presented. It is based on a flexible and modular software architecture （Framework Engine）, in which each functi...In this paper, the TAS-I （Thales Alenia Space-Italy） Test Bench for Robotics and Autonomy （TBRA） is presented. It is based on a flexible and modular software architecture （Framework Engine）, in which each functional module （representing the GNC subsystems） implements a key functionality of the GNC （Guidance Navigation and Control）. Modules communicate by means of standardised interfaces designed for exchange of necessary information among the modules composing the entire system. This approach permits the interchange-ability of each subsystem without affecting the overall functionalities of the GNC system. In this paper, the TBRA system, together with the implemented functional modules will be described. Tests results will be reported and future development will be discussed.展开更多
The great success of the Sojourner rover in the Mars Pathfinder mission set off a global upsurge of planetary exploration with autonomous wheeled mobile robots(WMRs),or rovers.Planetary WMRs are among the most intelli...The great success of the Sojourner rover in the Mars Pathfinder mission set off a global upsurge of planetary exploration with autonomous wheeled mobile robots(WMRs),or rovers.Planetary WMRs are among the most intelligent space systems that combine robotic intelligence(robint),virtual intelligence(virtint),and human intelligence(humint) synergetically.This article extends the architecture of the three-layer intelligence stemming from successful Mars rovers and related technologies in order to support the R&D of future tele-operated robotic systems.Double-layer human-machine interfaces are suggested to support the integration of humint from scientists and engineers through supervisory(Mars rovers) or three-dimensional(3D) predictive direct tele-operation(lunar rovers).The concept of multilevel autonomy to realize robint,in particular,the Coupled-Layer Architecture for Robotic Autonomy developed for Mars rovers,is introduced.The challenging issues of intelligent perception(proprioception and exteroception),navigation,and motion control of rovers are discussed,where the terrains' mechanical properties and wheel-terrain interaction mechanics are considered to be key.Double-level virtual simulation architecture to realize virtint is proposed.Key technologies of virtint are summarized:virtual planetary terrain modeling,virtual intelligent rover,and wheel-terrain interaction mechanics.This generalized three-layer intelligence framework is also applicable to other systems that require human intervention,such as space robotic arms,robonauts,unmanned deep-sea vehicles,and rescue robots,particularly when there is considerable time delay.展开更多
文摘In this study,a walking method that prevents a fall of the planetary exploration-legged rover is proposed.In the proposed walking method,the leg is sunk by giving vibration to the ground.The posture of the rover is changed to prevent a fall of the rover by sinking the leg.First,the relationship between the kind of vibration and the subsidence of the leg is confirmed.In this experimental result,the leg is shown to be easy to sink to the ground by giving vibration.Moreover,the larger the vibratory force is,the easier the leg sinks to the ground.Finally,the legged testbed walks on the loose ground with a slope using the proposed walking method.In this experimental result,the testbed is difficult to fall down when it uses the proposed walking.Moreover,the angle of a slope that the testbed can walk becomes large by using the proposed walking.
基金supported by the National Natural Science Foundation of China (Nos. 61233005 and 61503013)the National Basic Research Program of China (No. 2014CB744202)+2 种基金Beijing Youth Talent ProgramFundamental Science on Novel Inertial Instrument & Navigation System Technology LaboratoryProgram for Changjiang Scholars and Innovative Research Team in University (IRT1203) for their valuable comments
文摘Inertial navigation system/visual navigation system(INS/VNS) integrated navigation is a commonly used autonomous navigation method for planetary rovers. Since visual measurements are related to the previous and current state vectors(position and attitude) of planetary rovers, the performance of the Kalman filter(KF) will be challenged by the time-correlation problem. A state augmentation method, which augments the previous state value to the state vector, is commonly used when dealing with this problem. However, the augmenting of state dimensions will result in an increase in computation load. In this paper, a state dimension reduced INS/VNS integrated navigation method based on coordinates of feature points is presented that utilizes the information obtained through INS/VNS integrated navigation at a previous moment to overcome the time relevance problem and reduce the dimensions of the state vector. Equations of extended Kalman filter(EKF) are used to demonstrate the equivalence of calculated results between the proposed method and traditional state augmented methods. Results of simulation and experimentation indicate that this method has less computational load but similar accuracy when compared with traditional methods.
基金funded by the State Key Laboratory,China(KJW6142210210308)the National Natural Science Founda-tion of China(61806183).
文摘In order to ensure the safety and efficiency of planetary exploration rovers,path planning and tracking control of a planetary rover are expected to consider factors such as complex 3D terrain features,the motion constraints of the rover,traversability,etc.An improved path planning and tracking control method is proposed for planetary exploration rovers on rough terrain in this paper.Firstly,the kinematic model of the planetary rover is established.A 3D motion primitives library adapted to various terrains and the rover’s orientations is generated.The state expansion process and heuristic function of the A*algorithm are improved using the motion primitives and terrain features.Global path is generated by improved A*-based algorithm that satisfies the planetary rover’s kinematic constraints and the 3D terrain restrictions.Subsequently,an optional arc path set is designed based on the traversable capabilities of the planetary rover.Each arc path corresponds to a specific motion that determines the linear and angular velocities of the planetary rover.The optimal path is selected through the multi-objective evaluation function.The planetary rover is driven to accurately track the global path by sending optimal commands that corresponds to the optimal path for real-time obstacle avoidance.Finally,the path planning and tracking control method is effectively validated during a given mission through two simulation tests.The experiment results show that the improved A*-based algorithm reduces planning time by 30.05% and generates smoother paths than the classic A^(*) algorithm.The multi-objective arc-based method improves the rover’s motion efficiency,ensuring safer and quicker mission completion along the global path.
文摘In this paper, the TAS-I （Thales Alenia Space-Italy） Test Bench for Robotics and Autonomy （TBRA） is presented. It is based on a flexible and modular software architecture （Framework Engine）, in which each functional module （representing the GNC subsystems） implements a key functionality of the GNC （Guidance Navigation and Control）. Modules communicate by means of standardised interfaces designed for exchange of necessary information among the modules composing the entire system. This approach permits the interchange-ability of each subsystem without affecting the overall functionalities of the GNC system. In this paper, the TBRA system, together with the implemented functional modules will be described. Tests results will be reported and future development will be discussed.
基金supported by the National Natural Science Foundation of China(Grant No.61370033)National Basic Research Program of China(Grant No.2013CB035502)+4 种基金Foundation of Chinese State Key Laboratory of Robotics and Systems(Grant Nos.SKLRS201401A01,SKLRS-2014-MS-06)the Fundamental Research Funds for the Central Universities(Grant No.HIT.BRETIII.201411)Harbin Talent Programme for Distinguished Young Scholars(No.2014RFYXJ001)Postdoctoral Youth Talent Foundation of Heilongjiang Province,China(Grant No.LBH-TZ0403)the"111 Project"(Grant No.B07018)
文摘The great success of the Sojourner rover in the Mars Pathfinder mission set off a global upsurge of planetary exploration with autonomous wheeled mobile robots(WMRs),or rovers.Planetary WMRs are among the most intelligent space systems that combine robotic intelligence(robint),virtual intelligence(virtint),and human intelligence(humint) synergetically.This article extends the architecture of the three-layer intelligence stemming from successful Mars rovers and related technologies in order to support the R&D of future tele-operated robotic systems.Double-layer human-machine interfaces are suggested to support the integration of humint from scientists and engineers through supervisory(Mars rovers) or three-dimensional(3D) predictive direct tele-operation(lunar rovers).The concept of multilevel autonomy to realize robint,in particular,the Coupled-Layer Architecture for Robotic Autonomy developed for Mars rovers,is introduced.The challenging issues of intelligent perception(proprioception and exteroception),navigation,and motion control of rovers are discussed,where the terrains' mechanical properties and wheel-terrain interaction mechanics are considered to be key.Double-level virtual simulation architecture to realize virtint is proposed.Key technologies of virtint are summarized:virtual planetary terrain modeling,virtual intelligent rover,and wheel-terrain interaction mechanics.This generalized three-layer intelligence framework is also applicable to other systems that require human intervention,such as space robotic arms,robonauts,unmanned deep-sea vehicles,and rescue robots,particularly when there is considerable time delay.
