Path Planning for Tentacle Robots Using Soft Constraints

摘要: Tentacle robots – with many degrees of freedom one fixed end offer advantages over traditional in scenarios due to their enhanced flexibility and reachability. Planning practical paths for these devices is challenging high number (DOFs). Sampling-based path planners are a common approach the DOF planning problem associated tentacle but solutions found using such often not that they do take into account soft application-specific constraints. This paper describes general sample adjustment method which adjusts nodes edges generated by sampling-based within local neighborhood satisfy constraints problem. Experiments real simulated demonstrate our an effective enhancement basic probabilistic planner find paths.