Improved DWA-Based Local Path Planning for Multi-Robot Navigation

The Dynamic Window Approach (DWA) evaluates candidate motions for local robot navigation. This paper presents an Improved Dynamic Window Approach (IDWA) with two changes to trajectory evaluation. First, a distance threshold selects a near-term reference state on each predicted trajectory for heading evaluation. Second, an additional distance score combines the distance from the predicted endpoint to the local target with the minimum distance from the predicted trajectory to the obstacle-point set. A* provides global path guidance, while IDWA evaluates local candidate motions. Simulation comparisons report the trajectories, simulated navigation times, velocity responses, and smoothness of the complete IDWA configuration in the tested scenarios. Gazebo and indoor physical experiments also illustrate the operation of a multi-robot navigation system in obstacle-containing environments.