6R Serial Manipulator Space Path Planning Based on RRT

Ma, Chao; Zhang, Yong; Zhao, Qinjun; Bai, Kunfeng

doi:10.1109/ihmsc.2016.90

Cited by 10 publications

(1 citation statement)

References 8 publications

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“…To improve obstacle avoidance, the step size can be changed according to the number of obstacles in the surrounding environment [15]. Similarly, Ma et al [16] improved the advantage of RRT * in time and path, optimizing RRT * for the manipulator. You et al [17] preserved the initial tree, took it as the basis of pathfinding, and applied it to 9-degrees of freedom (DOF) manipulator pathfinding, with a much improved the obstacle avoidance efficiency.…”

Section: Introductionmentioning

confidence: 99%

Obstacle Avoidance Path Planning of a 4-DOF Weapon Arm Based on Improved RRT (RRT-H) Algorithm

Zou,

Guan,

et al. 2024

Mathematical Problems in Engineering

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To improve soldiers’ combat capability, weapon arms have a good development prospect. However, due to special work scenarios and tasks, new requirements are exerted on. Based on the fast-expanding random tree algorithm (RRT), path algorithm optimization (RRT-H) is proposed for the path planning of weapon arms. Overall path optimization is achieved by reducing the local path length with a closer path point planning to the obstacle. In a complex environment, the RRT-H algorithm can avoid local traps by guiding the new path extension direction and exploring multiple different paths in the map. The superiority of this algorithm is verified with 2D plane obstacle avoidance and pathfinding simulation experiments. Compared to RRT∗, RRT∗ smart, and information RRT∗, the RRT-H can obtain high-quality calculation results in a shorter time. After setting degrees of freedom (DOF) as that of variables, the algorithm is applied to the 4-DOF weapon arm, which confirms an effective reduction to the 4-DOF weapon arm’s motion costs.

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Section: Introductionmentioning

confidence: 99%