A Heuristic Rapidly-Exploring Random Trees Method for Manipulator Motion Planning

Rapidly-Exploring Random Trees: A New Tool for Path Planning

Intelligent bidirectional rapidly-exploring random trees for optimal motion planning in complex cluttered environments

The sampling based motion planning algorithm known as Rapidly-exploring Random Trees (RRT) has gained the attention of many researchers due to their computational efficiency and effectiveness. Recently, a variant of RRT called RRT* has been proposed that ensures asymptotic optimality. Subsequently its bidirectional version has also been introduced in the literature known as Bidirectional-RRT* (...

3D Motion Planning for Robot-Assisted Active Flexible Needle Based on Rapidly-Exploring Random Trees

An active flexible needle is a self-actuating needle that can bend in the tissue and reach the clinical targets while avoiding anatomic obstacles. In robot-assisted needlebased medical procedures, motion planning is a vital aspect of operations. It is challenging due to the nonholonomic motion of the needle and the presence of anatomic obstacles and sensitive organs that must be avoided. We pro...

Longitudinal Motion Planning for Slung-Loads Using Simplified Models and Rapidly-Exploring Random Trees

A randomized motion-planning approach to providing guidance for helicopters with under-slung loads is presented. Rapidly-exploring Random Trees are adapted to plan trajectories for simplified helicopter-load models. Four different planning models are tested against four different representative tasks. The poor performance of the baseline planner, and subsequent efforts to improve that performan...

Robotic Path Planning using Rapidly exploring Random Trees

Rapidly exploring Random Tree (RRT) path planning methods provide feasible paths between a start and goal point in configuration spaces containing obstacles, sacrificing optimality (eg. Shortest path) for speed. The raw resultant paths are generally jagged and the cost of extending the tree can increase steeply as the number of existing branches grow. This paper provides details of a speed-up m...