Hyper-redundant manipulators have been widely used in the complex and cluttered environment for achieving various kinds of tasks. In this article, we present two contributions. First, we provide a novel algorithm of relating forward and backward reaching inverse kinematic algorithm to velocity obstacles. Our optimization-based algorithm simultaneously handles the task space constraints, the joint limit constraints, and the collision-free constraints for hyper-redundant manipulators based on the generalized framework. Second, we present an extension of our inverse kinematic algorithm to collision avoidance for the hyper-redundant manipulators, where the workspaces may have different types of obstacles. We highlight the performance of our algorithm on hyper-redundant manipulators with various degrees of freedom. The results show that our algorithm has made full use of dexterity of hyper-redundant manipulators in complex environments, enhancing the performance and increasing the flexibility.

超冗余机械手已广泛用于复杂而混乱的环境中，以完成各种任务。在本文中，我们提出了两个建议。首先，我们提供了一种将向前和向后到达的逆运动学算法与速度障碍相关联的新颖算法。我们基于优化的算法可基于通用框架同时处理超冗余机械手的任务空间约束，关节极限约束和无碰撞约束。其次，我们提出了逆运动学算法的扩展，以防止超冗余机械手的碰撞避免，其中工作区可能具有不同类型的障碍物。我们重点介绍了我们算法在具有不同自由度的超冗余操纵器上的性能。