Study on Automatic Planning Method of Collision-Free Manipulator Path among Moving Obstacles.

Path planning among moving obstacles using spatial indexing

A method is presented for planning a pa th in t h e presence of moving obstacles. Given a se t of polygonal moving obstacles, we focus on generating a pa th for a mobile robot t h a t navigates in t h e two-dimensional plane. O u r methodology is t o include t ime as one of t h e dimensions of t h e model world. T h i s allows u s t o regard the moving obstacles as being s ta t ionary in t h e ...

Collision-free Path Planning Based on Clustering

The goal of collision-free path planning is to find a continuous path from a starting position to goal position without any collisions. The collision-free path planning is a critical skill in mobile robot applications, and by now it is still a tough problem because mobile robots would easily run into the situation of planning for the current path while neglecting the global goal. In this paper,...

Centralized Path Planning for Multi-aircraft in the Presence of Static and Moving Obstacles

This article proposes a new approach for centralized path planning of multiple aircraft in presence of the obstacle-laden environment under low flying rules. The problem considers as a unified nonlinear constraint optimization problem. The minimum time and control investigate as the cost functions and the maximum velocity and power consider as the constraints. The pseudospectral method applies ...

Velocity Planning for a Robot Moving along the Shortest Straight Line Path Among Moving Obstacles

Reactive planning under uncertainty among moving obstacles

This paper addresses the problem of navigation of complex systems in dynamic environments under uncertainty. Such environments impose a hard real time constraint. However, computing a complete motion to the goal within a limited time is impossible to achieve in most real situations. The Partial Motion Planning (PMP) approach presented in [1] is used to address the planning problem. However, for...