Robot navigation that moves obstacles to reach blocked goals
Towards Path-Creative Navigation: Robot Navigation through Embodied Interaction
Robotics
Summary
Robots often get stuck when paths are blocked by things like movable objects, doors, or people. This paper introduces a way for robots to not just find paths but also move or interact with obstacles to create new routes. The authors built a system that combines sensors and robot movement to decide when and how to push or avoid obstacles safely. They tested their system in simulations and real-world tasks where normal navigation fails, showing it can complete more tasks by using these interactions.
What this means in practice
- •For warehouse robotics teams: Enable robots to reposition movable obstacles and open pathways to navigate cluttered warehouse aisles more effectively.
- •For service robot developers: Design service robots that can safely interact with people and movable objects to complete navigation tasks in dynamic indoor environments.$Commercial implications: This technology allows development of robots that interact with the environment to perform navigation in crowded homes or offices, enabling commercial service robots with better autonomy.
Authors
Haoyu Xi, Siwei Cheng, Xiangyuan Liu, Brenda Li, Wei Zhang
Abstract
Autonomous navigation in cluttered and constrained environments typically assumes a fixed environment and searches only for paths within existing free space. However, a route can be blocked by an articulated structure, a movable object, or a pedestrian, and reaching the goal may therefore require appropriate embodied interaction with the environment. This paper formulates Path-Creative Navigation (PCN), a navigation paradigm in which the robot recovers free space by coordinating locomotion and embodied interaction, and addresses one class of PCN tasks with a mapless framework. The vision-LiDAR-odometry framework integrates local observations, obstacle geometry, and robot-state estimates through a unified navigation system, providing stable semantic and geometric information for navigation and interaction. The traversability-aware decision method utilizes visual and LiDAR distance information to determine whether a blockage is actionable and whether it can be safely bypassed, enabling the robot to interact only when necessary while supporting articulated structure pushing, movable object pushing, obstacle avoidance, and pedestrian requests. We design simulation scenarios and evaluate different methods in both simulation and two real-world tasks that cannot be completed by conventional navigation alone without embodied interaction. These results demonstrate that our framework achieves higher task completion than the baseline methods by coordinating navigation and interaction in cluttered and constrained environments. Code is available at:{https://anonymous.4open.science/r/path-creative-navigation/}.