Model-Based Analysis of Autonomous Self-Adaptive Cooperating Robots

Validation and verification (V&V) is an integral part of systems engineering that allows the designer to establish the correctness of a system as well as analyze its robustness in the presence of disturbances and failures. Robustness analysis of autonomous self-organizing and adaptive systems presents new challenges. Such systems evolve at run-time to respond to changes in need and context. This paper considers the analysis of self-adaptive cooperating robots that are targeted for the pursuer-evader class of problems and applications in space/air/ground. This problem is a particularly challenging topic in cooperative robotics research because it includes several different capabilities characteristic of cooperative robotics enabled applications such as target assignment, path planning and collision avoidance. In this paper, we describe the initial foundation of a model-based framework that enable robustness analysis of certain adaptive and self-configuring aspects of the performance of such systems. In particular, we concentrate on the analysis of a collision-avoidance strategy employed to prevent collisions between pursuers. The work presented in this paper was conducted at the Lockheed Martin Advanced Technology Center and was influenced by a prior VVIACS project (Validation & Verification of Intelligent and Adaptive Control Systems).