Path Planning Games
This work addresses path planning for robotic agents by providing a novel economic perspective, though it appears incremental as it builds on existing game theory concepts.
The paper tackles the problem of strategic interactions in multi-agent path planning by introducing a game-theoretic framework that trades off efficiency and safety, showing through case studies that safety is often significantly compromised in non-cooperative settings compared to cooperative solutions.
Path planning is a fundamental and extensively explored problem in robotic control. We present a novel economic perspective on path planning. Specifically, we investigate strategic interactions among path planning agents using a game theoretic path planning framework. Our focus is on economic tension between two important objectives: efficiency in the agents' achieving their goals, and safety in navigating towards these. We begin by developing a novel mathematical formulation for path planning that trades off these objectives, when behavior of other agents is fixed. We then use this formulation for approximating Nash equilibria in path planning games, as well as to develop a multi-agent cooperative path planning formulation. Through several case studies, we show that in a path planning game, safety is often significantly compromised compared to a cooperative solution.