Safe Motion Planning for Imprecise Robotic Manipulators by Minimizing Probability of Collision
Safe Motion Planning for Imprecise Robotic Manipulators by Minimizing Probability of Collision
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DOI：
10.1007/978-3-319-28872-7_39
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发表时间：
2013
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影响因子：
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通讯作者：
Wen Sun;Luis G. Torres;J. V. D. Berg;R. Alterovitz
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作者：
Wen Sun;Luis G. Torres;J. V. D. Berg;R. Alterovitz
由于合规性要求、成本限制和尺寸限制，设计用于家庭辅助和新外科手术的机器人操纵器通常在其致动中具有显著的不确定性。我们介绍了一种新的集成运动规划和控制算法的机器人机械手，使安全的优先考虑明确考虑不必要的碰撞的概率。首先，我们提出了一种快速的方法来估计碰撞概率的假设下，高斯运动和感知不确定性的机器人机械手的运动计划。我们的方法可以快速计算工作空间中障碍物的距离，并使用牛顿方法将此信息适当地转换到配置空间中，以估计配置空间中最相关的碰撞点。然后，我们提出了一个基于采样的运动规划的基础上执行多个独立的快速探索随机树，返回一个计划，在合理的假设下，渐近收敛到一个计划，最大限度地减少估计的碰撞概率。我们证明了我们的计划在模拟的速度和安全性（1）3-D机械手与6自由度，和（2）同心管机器人，触手般的机器人设计用于外科手术应用。
Robotic manipulators designed for home assistance and new surgical procedures often have significant uncertainty in their actuation due to compliance requirements, cost constraints, and size limits. We introduce a new integrated motion planning and control algorithm for robotic manipulators that makes safety a priority by explicitly considering the probability of unwanted collisions. We first present a fast method for estimating the probability of collision of a motion plan for a robotic manipulator under the assumptions of Gaussian motion and sensing uncertainty. Our approach quickly computes distances to obstacles in the workspace and appropriately transforms this information into the configuration space using a Newton method to estimate the most relevant collision points in configuration space. We then present a sampling-based motion planner based on executing multiple independent rapidly exploring random trees that returns a plan that, under reasonable assumptions, asymptotically converges to a plan that minimizes the estimated collision probability. We demonstrate the speed and safety of our plans in simulation for (1) a 3-D manipulator with 6 DOF, and (2) a concentric tube robot, a tentacle-like robot designed for surgical applications.