Navigation & SLAM

Dynamic Window Approach (DWA)

Dynamic Window Approach (DWA) is a local obstacle-avoidance and velocity-planning method for mobile robots, introduced by Fox, Burgard, and Thrun in 1997. It samples candidate translational and rotational velocities from the window reachable within one control cycle given acceleration limits, simulates short-horizon arcs, discards colliding ones, and scores the rest on heading, clearance, and speed. DWA has long been a standard local planner in ROS navigation stacks.

Why it matters for physical AI

Decades after publication, DWA-style local planners still execute the final meters of most AMR motion, forming the reactive safety layer beneath global planners and, increasingly, learned navigation policies.