비홀로노믹 모바일 매니퓰레이터의 영공간 투영에 기반한 충돌 회피
Collision Avoidance Based on Null Space Projection for a Nonholonomic Mobile Manipulator
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초록
Since the mobile platform and the manipulator mounted on it move at the same time in a mobile manipulator, the risk of mutual collision increases. Most of the studies on collision avoidance of mobile manipulators cannot be applied to differential drive type mobile platforms or the end-effector tends to deviate from the desired trajectory for collision avoidance. In this study, a collision avoidance algorithm based on null space projection (CANS) that solves these two problems is proposed. To this end, a modified repulsive force that overcomes the non-holonomic constraints of a mobile platform is generated by adding a virtual repulsive force in the direction of its instantaneous velocity. And by converting this repulsive force into a repulsive velocity and applying it to the null space, the end-effector of the robot avoids a collision while moving along its original trajectory. The proposed CANS algorithm showed excellent performance through self-collision avoidance tests and door opening tests.
Abstract
Since the mobile platform and the manipulator mounted on it move at the same time in a mobile manipulator, the risk of mutual collision increases. Most of the studies on collision avoidance of mobile manipulators cannot be applied to differential drive type mobile platforms or the end-effector tends to deviate from the desired trajectory for collision avoidance. In this study, a collision avoidance algorithm based on null space projection (CANS) that solves these two problems is proposed. To this end, a modified repulsive force that overcomes the non-holonomic constraints of a mobile platform is generated by adding a virtual repulsive force in the direction of its instantaneous velocity. And by converting this repulsive force into a repulsive velocity and applying it to the null space, the end-effector of the robot avoids a collision while moving along its original trajectory. The proposed CANS algorithm showed excellent performance through self-collision avoidance tests and door opening tests.
참고문헌 (9)
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