When a curling rock slides on an ice sheet with an initial rotation,a lateral movement occurs,which is known as the curling phenomenon.The force of friction between the curling rock and the ice sheet changes continual...When a curling rock slides on an ice sheet with an initial rotation,a lateral movement occurs,which is known as the curling phenomenon.The force of friction between the curling rock and the ice sheet changes continually with changes in the environment;thus,the sport of curling requires great skill and experience.The throwing of the curling rock is a great challenge in robot design and control,and existing curling robots usually adopt a combination scheme of a wheel chassis and gripper that differs significantly from human throwing movements.A hexapod curling robot that imitates human kicking,sliding,pushing,and curling rock rotating was designed and manufactured by our group,and completed a perfect show during the Beijing 2022 Winter Olympics Games.Smooth switching between the walking and throwing tasks is realized by the robot’s morphology transformation based on leg configuration switching.The robot’s controlling parameters,which include the kicking velocity v_(k),pushing velocity v_(p),orientation angle θc,and rotation velocityω,are determined by aiming and sliding models according to the estimated equivalent friction coefficientμ_(equ)and ratio e of the front and back frictions.The stable errors between the target and actual stopping points converge to 0.2 and 1.105 m in the simulations and experiments,respectively,and the error shown in the experiments is close to that of a well-trained wheelchair curling athlete.This robot holds promise for helping ice-makers rectify ice sheet friction or assisting in athlete training.展开更多
The current gait planning for legged robots is mostly based on human presets,which cannot match the flexible characteristics of natural mammals.This paper proposes a gait optimization framework for hexapod robots call...The current gait planning for legged robots is mostly based on human presets,which cannot match the flexible characteristics of natural mammals.This paper proposes a gait optimization framework for hexapod robots called Smart Gait.Smart Gait contains three modules:swing leg trajectory optimization,gait period&duty optimization,and gait sequence optimization.The full dynamics of a single leg,and the centroid dynamics of the overall robot are considered in the respective modules.The Smart Gait not only helps the robot to decrease the energy consumption when in locomotion,mostly,it enables the hexapod robot to determine its gait pattern transitions based on its current state,instead of repeating the formalistic clock-set step cycles.Our Smart Gait framework allows the hexapod robot to behave nimbly as a living animal when in 3D movements for the first time.The Smart Gait framework combines offline and online optimizations without any fussy data-driven training procedures,and it can run efficiently on board in real-time after deployment.Various experiments are carried out on the hexapod robot LittleStrong.The results show that the energy consumption is reduced by 15.9%when in locomotion.Adaptive gait patterns can be generated spontaneously both in regular and challenge environments,and when facing external interferences.展开更多
This paper proposes a novel continuous footholds optimization method for legged robots to expand their walking ability on complex terrains.The algorithm can efficiently run onboard and online by using terrain percepti...This paper proposes a novel continuous footholds optimization method for legged robots to expand their walking ability on complex terrains.The algorithm can efficiently run onboard and online by using terrain perception information to protect the robot against slipping or tripping on the edge of obstacles,and to improve its stability and safety when walking on complex terrain.By relying on the depth camera installed on the robot and obtaining the terrain heightmap,the algorithm converts the discrete grid heightmap into a continuous costmap.Then,it constructs an optimization function combined with the robot’s state information to select the next footholds and generate the motion trajectory to control the robot’s locomotion.Compared with most existing footholds selection algorithms that rely on discrete enumeration search,as far as we know,the proposed algorithm is the first to use a continuous optimization method.We successfully implemented the algorithm on a hexapod robot,and verified its feasibility in a walking experiment on a complex terrain.展开更多
基金funded by the National Natural Science Foundation of China(92248303).
文摘When a curling rock slides on an ice sheet with an initial rotation,a lateral movement occurs,which is known as the curling phenomenon.The force of friction between the curling rock and the ice sheet changes continually with changes in the environment;thus,the sport of curling requires great skill and experience.The throwing of the curling rock is a great challenge in robot design and control,and existing curling robots usually adopt a combination scheme of a wheel chassis and gripper that differs significantly from human throwing movements.A hexapod curling robot that imitates human kicking,sliding,pushing,and curling rock rotating was designed and manufactured by our group,and completed a perfect show during the Beijing 2022 Winter Olympics Games.Smooth switching between the walking and throwing tasks is realized by the robot’s morphology transformation based on leg configuration switching.The robot’s controlling parameters,which include the kicking velocity v_(k),pushing velocity v_(p),orientation angle θc,and rotation velocityω,are determined by aiming and sliding models according to the estimated equivalent friction coefficientμ_(equ)and ratio e of the front and back frictions.The stable errors between the target and actual stopping points converge to 0.2 and 1.105 m in the simulations and experiments,respectively,and the error shown in the experiments is close to that of a well-trained wheelchair curling athlete.This robot holds promise for helping ice-makers rectify ice sheet friction or assisting in athlete training.
基金Supported by National Key Research and Development Program of China(Grant No.2021YFF0306202).
文摘The current gait planning for legged robots is mostly based on human presets,which cannot match the flexible characteristics of natural mammals.This paper proposes a gait optimization framework for hexapod robots called Smart Gait.Smart Gait contains three modules:swing leg trajectory optimization,gait period&duty optimization,and gait sequence optimization.The full dynamics of a single leg,and the centroid dynamics of the overall robot are considered in the respective modules.The Smart Gait not only helps the robot to decrease the energy consumption when in locomotion,mostly,it enables the hexapod robot to determine its gait pattern transitions based on its current state,instead of repeating the formalistic clock-set step cycles.Our Smart Gait framework allows the hexapod robot to behave nimbly as a living animal when in 3D movements for the first time.The Smart Gait framework combines offline and online optimizations without any fussy data-driven training procedures,and it can run efficiently on board in real-time after deployment.Various experiments are carried out on the hexapod robot LittleStrong.The results show that the energy consumption is reduced by 15.9%when in locomotion.Adaptive gait patterns can be generated spontaneously both in regular and challenge environments,and when facing external interferences.
基金supported by the National Key R&D Program of China(Grant No.2021YFF0306202).
文摘This paper proposes a novel continuous footholds optimization method for legged robots to expand their walking ability on complex terrains.The algorithm can efficiently run onboard and online by using terrain perception information to protect the robot against slipping or tripping on the edge of obstacles,and to improve its stability and safety when walking on complex terrain.By relying on the depth camera installed on the robot and obtaining the terrain heightmap,the algorithm converts the discrete grid heightmap into a continuous costmap.Then,it constructs an optimization function combined with the robot’s state information to select the next footholds and generate the motion trajectory to control the robot’s locomotion.Compared with most existing footholds selection algorithms that rely on discrete enumeration search,as far as we know,the proposed algorithm is the first to use a continuous optimization method.We successfully implemented the algorithm on a hexapod robot,and verified its feasibility in a walking experiment on a complex terrain.