Automated collision avoidance developed within a mixed reality system

Abstract

As the use of unmanned systems becomes more prevalent in both commercial and military applications, increasing performance requirements have led to a greater demand for automation. The ability for an autonomous unmanned system to perform basic tasks reliably reduces the operator’s cognitive tasks and workload, which could facilitate the control of multiple systems by a single operator. A key component for autonomous systems in many applications is the ability to perform reliable collision avoidance. A critical part of collision avoidance, often overlooked in existing algorithms, is that only a small set of velocities are actually reachable by the platform due to physical limitations or environmental factors. This paper presents the 3D Automated Velocity Obstacle Collision Avoidance (AVOCA) algorithm; a velocity obstacle based collision avoidance system that uses Kinematic Velocity Constraints (KVCs) to bind the velocity selection process. Results for AVOCA are presented from both simulation and experimentation using physical and virtual platforms in a Mixed Reality (MR) environment.