Navigation improves using robot footprint clearance over sensor range
DCLP++: Learning to Navigate with Footprint Clearance and Relative Motion
Robotics
Summary
Robots need to move safely around moving obstacles, and how they sense their surroundings matters. The authors tried a new way for a robot to understand its space by measuring distances from its shape (footprint) rather than from its sensor. This helped the robot navigate better in tests with moving obstacles, achieving success more often. They also tested adding movement information but found it less clear if this helped. More work is needed to see if this method works well for different robot shapes and conditions.
What this means in practice
- •For robotics developers: Improve robot local navigation by using footprint-based distance measurements for better obstacle avoidance in dynamic environments.
- •For autonomous vehicle engineers: Develop safer navigation policies in crowded or dynamic scenarios by integrating robot footprint clearance features into LiDAR processing.
Authors
Shanze Wang, Wei Zhang
Abstract
We present DCLP++, a local navigation frameworkthat uses footprint clearance as the geometric basis for studying relative motion features in dynamic environments. Each valid LiDAR return is mapped to its shortest Euclidean distance from the filled robot footprint before reciprocal encoding, replacing distance from the sensor with distance to the occupied body. Radial measurementsor simulated planar relative velocities provide short-horizon features without static-dynamic labels in the policy input. A preliminary study uses a rectangular robot with a speed limit of 1 m/s among 20 moving obstacles. On 100 fixed validation tasks, two selected training seeds yield mean success rates of 42% with sensor rangeand 70% with footprint clearance after 200,000 environment steps.Motion variants show mixed additional gains. These results supportthe clearance-based observation in the evaluated setting; reliable motion benefits and transfer across robots require further evaluation.