TL;DR
Compared with ACO algorithm, RRT* algorithm, RRT* algorithm and Bias-RRT algorithm, the OS-RRT algorithm can plan a better path quality in a shorter time and requires fewer sampling points, which verifies the excellent path planning performance of the OS-RRT algorithm.
An improved algorithm with dual-tree collaborative characteristics—KQ-RRT*-Connect is proposed, which reduces the initial path calculation time of O-RRT* by 90%, the number of iterations required by 85%, and the path cost by more than 4.5%.
The proposed OB-RRT algorithm incorporates obstacle-node information derived from collision samples to guide tree expansion and improve exploration efficiency, and is validated on a 6-DoF robotic arm in a catenary maintenance scenario using a digital twin framework.
In order to solve the problems of strong sampling randomness, slow convergence speed, long and tortuous path and poor adaptability of narrow channel in the path planning of robotic arm by using the rapid exploration random tree (RRT) algorithm, a hierarchical adaptive smooth pruning RRT* (HASP-RRT*) algorithm is propos...
A novel multi-strategy integrated RRT* (M-RRT*) path planning framework that enables coordinated optimization across all modules is proposed, exhibiting more pronounced comprehensive advantages in complex maze and narrow passage scenarios.
Robot path planning is a key core technology for realizing autonomous navigation of robots. Among them, the A* algorithm has been widely used due to its good balance between path optimality and search efficiency. However, the traditional A* algorithm faces problems such as excessive expansion nodes, numerous path infle...
A hybrid path planning algorithm that integrates an improved Bidirectional Rapidly-exploring Random Tree (BI-RRT) for global guidance with an enhanced Dynamic Window Approach (DWA) for local execution that improves search efficiency and maintains 100% success rate across tested environments.
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