Collision Avoidance from Multiple Passive Agents with Partially Predictable Behavior
Source abstract
Abstract
Navigating a robot in a dynamic environment is a challenging task, especially when the behavior of other agents such as pedestrians, is only partially predictable. Also, the kinodynamic constraints on robot motion add an extra challenge. This paper proposes a novel navigational strategy for collision avoidance of a kinodynamically constrained robot from multiple moving passive agents with partially predictable behavior. Specifically, this paper presents a new approach to identify the set of control inputs to the robot, named control obstacle, which leads it towards a collision with a passive agent moving along an arbitrary path. The proposed method is developed by generalizing the concept of nonlinear velocity obstacle (NLVO), which is used to avoid collision with a passive agent, and takes into account the kinodynamic constraints on robot motion. Further, it formulates the navigational problem as an optimization problem, which allows the robot to make a safe decision in the presence of various sources of unmodelled uncertainties. Finally, the performance of the algorithm is evaluated for different parameters and is compared to existing velocity obstacle-based approaches. The simulated experiments show the excellent performance of the proposed approach in term of computation time and success rate.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Robotic Path Planning Algorithms · Robotics and Sensor-Based Localization · Distributed Control Multi-Agent Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Mechatronics Engineering, Hanyang University ERICA Campus, Ansan 15588, Korea
Department of Robot Engineering, Hanyang University ERICA Campus, Ansan 15588, Korea
School of Mechanical and Manufacturing Engineering (SMME), National University of Science and Techonology (NUST), Islamabad 44000, Pakistan
References (28)
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