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Planning and Fast Replanning Safe Motions for Humanoid Robots

机译:规划和快速重新规划人形机器人的安全运动

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This paper introduces effective numerical methods for the planning and fast replanning of safe motions to ensure the safety, balance, and integrity of humanoid robots over the whole motion duration. Our safe methods do not depend on, nor are connected to, any type of modeling or constraints. To plan safe motions, certain constraints have to be satisfied over a continuous interval of time. Classical methods revert to time-grid discretization, which can be risky for the robot. We introduce a hybrid method to plan safe motions, which combines a classical unsafe method with a verification step that checks constraint violation and computes excess by the usage of interval analysis. When the robot meets unexpected situations, it has to replan a new motion, which is often too time consuming. Hence, we introduce a new method to rapidly replan safe motions, i.e., in less than 2 s CPU time. It computes offline feasible subsets in the vicinity of safe motions and finds online a solution in these subsets without actually recomputing the nonlinear constraints. Our methods are validated by the use the HOAP-3 robot, where the motions are run with no balance controller.
机译:本文介绍了用于安全运动的计划和快速重新规划的有效数值方法,以确保类人机器人在整个运动过程中的安全性,平衡性和完整性。我们的安全方法不依赖于任何类型的建模或约束,也不与之相关。为了计划安全运动,必须在连续的时间间隔内满足某些约束条件。经典方法恢复为时间网格离散化,这对于机器人来说可能是危险的。我们介绍了一种用于计划安全运动的混合方法,该方法将经典的不安全方法与验证步骤相结合,该方法检查约束违规并通过使用间隔分析来计算超出量。当机器人遇到意外情况时,它必须重新计划新的动作,这通常会很费时。因此,我们引入了一种新方法来快速重新计划安全运动,即在不到2 s的CPU时间内。它计算安全运动附近的离线可行子集,并在线上找到这些子集中的解决方案,而无需实际重新计算非线性约束。我们的方法通过使用HOAP-3机器人进行了验证,该机器人在没有平衡控制器的情况下运行运动。

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