This study presents a straightforward method to teach robots to use tools.Teaching robots is crucial in quickly deploying and reconfiguring robots in next-generation factories.Conventional methods require third-party ...This study presents a straightforward method to teach robots to use tools.Teaching robots is crucial in quickly deploying and reconfiguring robots in next-generation factories.Conventional methods require third-party systems like wearable devices or complicated vision system to capture,analyse,and map human grasps,motion,and tool poses to robots.These systems assume lots of experience from their users.Unlike the conventional methods,this study does not involve learning human motion and skills.Instead,it only learns the object goal poses from the human user whilst employs regrasp planning to generate robot motion.The method is most suitable for a robot to learn the usage of electric tools that can be operated by simply switching on and off.The proposed method is validated using a dual-arm robot with hand-mounted cameras and several tools.Experimental results show that the proposed method is robust,feasible,and simple to teach robots.It can find a collision-free and kino-dynamic feasible grasp sequences and motion trajectories when the goal pose is reachable.The method allows the robot to automatically choose placements or handover considering the surrounding environment as intermediate states to change the pose of the tool and use tools following human demonstrations.展开更多
This paper presents a remotely operated robotic system that includes two mobile manipulators to extend the functional capabilities of a human body.Compared with previous tele-operation or robotic body extension system...This paper presents a remotely operated robotic system that includes two mobile manipulators to extend the functional capabilities of a human body.Compared with previous tele-operation or robotic body extension systems,using two mobile manipulators helps with enlarging the workspace and allowing manipulation of large or long objects.The system comprises a joystick for controlling the mobile base and robotic gripper,and a motion capture system for controlling the arm poses.They together enable tele-operated dual-arm and large-space manipulation.In the experiments,a human tele-operator controls the two mobile robots to perform tasks such as handover,long object manipulation,and cooperative manipulation.The results demonstrated the effectiveness of the proposed system,resulting in extending the human body to a large space while keeping the benefits of having two limbs.展开更多
文摘This study presents a straightforward method to teach robots to use tools.Teaching robots is crucial in quickly deploying and reconfiguring robots in next-generation factories.Conventional methods require third-party systems like wearable devices or complicated vision system to capture,analyse,and map human grasps,motion,and tool poses to robots.These systems assume lots of experience from their users.Unlike the conventional methods,this study does not involve learning human motion and skills.Instead,it only learns the object goal poses from the human user whilst employs regrasp planning to generate robot motion.The method is most suitable for a robot to learn the usage of electric tools that can be operated by simply switching on and off.The proposed method is validated using a dual-arm robot with hand-mounted cameras and several tools.Experimental results show that the proposed method is robust,feasible,and simple to teach robots.It can find a collision-free and kino-dynamic feasible grasp sequences and motion trajectories when the goal pose is reachable.The method allows the robot to automatically choose placements or handover considering the surrounding environment as intermediate states to change the pose of the tool and use tools following human demonstrations.
基金supported by the UKRI Future Leaders Fellowship[MR/V025333/1](RoboHike)and the UCL-Osaka University Strategic Partner Fund 2021.
文摘This paper presents a remotely operated robotic system that includes two mobile manipulators to extend the functional capabilities of a human body.Compared with previous tele-operation or robotic body extension systems,using two mobile manipulators helps with enlarging the workspace and allowing manipulation of large or long objects.The system comprises a joystick for controlling the mobile base and robotic gripper,and a motion capture system for controlling the arm poses.They together enable tele-operated dual-arm and large-space manipulation.In the experiments,a human tele-operator controls the two mobile robots to perform tasks such as handover,long object manipulation,and cooperative manipulation.The results demonstrated the effectiveness of the proposed system,resulting in extending the human body to a large space while keeping the benefits of having two limbs.
