Computational receding horizon approach to safe trajectory tracking

摘要: This paper presents a receding horizon methodology for trajectory tracking with safe collision conflict resolution multiple autonomous vehicles. The proposed decentralized scheme is formulated in discrete-time domain where each vehicle's objective function represents deviations from its desired trajectory. safety constraints penalizing if two or more vehicles get closer than prescribed distance are incorporated using avoidance functions. These functions added to the be minimized by vehicle. They also represent coupling elements allowing implicit coordination among case of possible collision. Vehicles modeled unicycle model subject bounds on both velocity and angular velocity. optimization performed vehicle uses sequential quadratic programming method which well suited minimization scalar nonlinear equality (dynamic model) inequality (velocity conditions). Outputs process kinematic control inputs For symmetric cases gradient based methods known perform poorly (such as singular cases) limit cycle implemented modify segments trajectories leading feasible solutions terms