Collision Prevention Strategy Using Sparse 2D Spatial Information for Indoor Mobile Robots

Abstract

This paper proposes a collision prevention strategy for indoor mobile robots that utilizes a low-cost two-dimensional (2D) range scanner. The use of indoor mobile robots for versatile tasks, such as serving, cleaning, and delivery, has been increasing. As these robots navigate in environments with dynamic obstacles of arbitrary sizes and shapes that move at irregular speeds and directions, sophisticated motion planning is essential to ensure safe and successful task completion. Previous works have relied on object-wise detection and tracking methods that demand significant computing resources and rich information. However, these approaches are challenging to apply for commercial robots that require light computation and guaranteed safety. In this paper, we propose a novel and straightforward strategy that predicts the behavior of dynamic obstacles using agglomerated dynamic points-based trajectory envelope estimation (ADTE), instead of the conventional object-wise approach. We also introduce the stop trigger as a practical and safe strategy that uses the predicted information. The stop trigger operates independently of the primary motion planning module to isolate prediction uncertainty. The proposed strategy was verified through robot testing and simulation with standardized test scenarios defined in ISO 18646–2. The robot testing was officially conducted by an authorized organization. The results demonstrate the effectiveness of the proposed strategy in preventing collisions with moving obstacles.