Goal-predictive robotic teleoperation from noisy sensors.
ICRA(2017)
摘要
Robotic teleoperation from a human operatoru0027s pose demonstrations provides an intuitive and effective means of control that has been made feasible by improvements in sensor technologies in recent years. However, the imprecision of low-cost depth cameras and the difficulty of calibrating a frame of reference for the operator introduce inefficiencies in this process when performing tasks that require interactions with objects in the robotu0027s workspace. We develop a goal-predictive teleoperation system that aids in “de-noising” the controls of the operator to be more goal-directed. Our approach uses inverse optimal control to predict the intended object of interaction from the current motion trajectory in real time and then adapts the degree of autonomy between the operatoru0027s demonstrations and autonomous completion of the predicted task. We evaluate our approach using the Microsoft Kinect depth camera as our input sensor to control a Rethink Robotics Baxter robot.
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关键词
goal-predictive robotic teleoperation,noisy sensors,human operator pose demonstrations,sensor technologies,low-cost depth cameras,robot workspace,goal-predictive teleoperation system,inverse optimal control,motion trajectory,autonomous completion,Microsoft Kinect depth camera,input sensor,Rethink Robotics Baxter robot
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