NPQ‐RRT ^∗: An Improved RRT ^∗ Approach to Hybrid Path Planning

Abstract

In recent years, the path planning of robot has been a hot research direction, and multirobot formation has practical application prospect in our life. This article proposes a hybrid path planning algorithm applied to robot formation. The improved Rapidly Exploring Random Trees algorithm PQ-RRT ∗ with new distance evaluation function is used as a global planning algorithm to generate the initial global path. The determined parent nodes and child nodes are used as the starting points and target points of the local planning algorithm, respectively. The dynamic window approach is used as the local planning algorithm to avoid dynamic obstacles. At the same time, the algorithm restricts the movement of robots inside the formation to avoid internal collisions. The local optimal path is selected by the evaluation function containing the possibility of formation collision. Therefore, multiple mobile robots can quickly and safely reach the global target point in a complex environment with dynamic and static obstacles through the hybrid path planning algorithm. Numerical simulations are given to verify the effectiveness and superiority of the proposed hybrid path planning algorithm.

Path Planning Techniques for Real-Time Multi-Robot Systems: A Systematic Review

“…However, classical path planning approaches continue to be relevant and serve as a valuable foundation for modern path planning techniques. A variety of deterministic path planning techniques have been applied, including cell decomposition techniques [35][36][37][38][39][40][41], artificial potential field techniques [46][47][48], and sampling-based techniques [44,45]. The subsequent sections will explore the three subdivisions of traditional methods.…”

“…Based on the experimental results applied on a heterogeneous system (UAV-UGV), the RRT algorithm is robust to uncertainties and capable of real-time replanning, but it exhibits some limitations related to scalability. The authors in [45] enhance the conventional RRT* algorithm and propose a New Potential Quick-RRT* (NPQRRT*), which incorporates the attitude adjustment angle of the robot into the path planning process. Furthermore, the algorithm is expanded to address the path planning problem in a system with multiple mobile robots.…”

“…UGV [36,37,39], [41,45,57], [62,69,71], [47,59,61], [66,67,70], [73] Centralized Humanoid [64,72] -Single point of failure.…”

Multi-Objective Point Motion Planning for Assembly Robotic Arm Based on IPQ-RRT* Connect Algorithm

“…The second type of map was set up as a more complex folding line map. The starting point coordinates are (20,10), and the target coordinates are (80, 90). In the figure, the black point and the rose red point serve as the start and end point, respectively.…”

“…Since PQ-RRT* only considers static path planning and does not take path planning in dynamic environments into account, it has limitations. Therefore, Yu et al improved New Potential Quick-RRT* (NPQ-RRT*) for UAV applications [20]. After completing the path planning, in order to ensure the quality of the path, it is also necessary to optimize the planning path with smoothing [21,22].…”