# Density-Based Detection Rapid Exploration Random Tree for Multirobot Formation Cooperative Path Planning

## TL;DR

This paper introduces a new multirobot path planning method that improves path generation and obstacle avoidance for robot formations.

## Contribution

A novel DDRRT algorithm and enhanced artificial potential field for multirobot formation control are proposed.

## Key findings

- The DDRRT algorithm efficiently generates global paths for leader robots while avoiding redundant exploration.
- Optimized repulsion fields and rotational potential fields improve local obstacle avoidance and target reachability.
- Formation transformation using polar coordinates enhances the control and adaptability of robot formations in complex environments.

## Abstract

This paper proposes a multirobot formation path planning method based on the leader–follower formation control method to ensure smooth operation in the multirobot formation control area. First, on the basis of the rapidly exploring random tree (RRT), a density detection rapidly exploring random tree (DDRRT) algorithm is designed to avoid repeated exploration of by the RRT, to quickly generate a global path from the starting point to the destination for the leader robot, and to propose a rope shrinkage path optimization mechanism for path optimization. Second, the repulsion field function in the artificial potential field (APF) is optimized for local collaborative obstacle avoidance to enable multiple robots, and a rotational potential field is introduced to solve the problems of unreachable targets and local oscillations. Finally, a control law based on consistency control is used to control the followers and introduce a formation change mechanism based on polar coordinate transformation to enhance the formation control capability. The simulation results show that the proposed strategy can provide high-quality paths for robot formations in multiple obstacle areas and guide robot formations to avoid various local obstacles quickly through formation transformation.