Ethernet: distributed packet switching for local computer networks
Communications of the ACM
Dynamic Motion Planning for Mobile Robots Using Potential Field Method
Autonomous Robots
The focussed D* algorithm for real-time replanning
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
A unified approach to semi-autonomous control of passenger vehicles in hazard avoidance scenarios
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Roadmap-based motion planning in dynamic environments
IEEE Transactions on Robotics
Survey Constrained model predictive control: Stability and optimality
Automatica (Journal of IFAC)
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Replanning is a powerful mechanism for controlling robot motion under hard constraints and unpredictable disturbances, but it involves an inherent tradeoff between the planner's power (e.g., a planning horizon or time cutoff) and its responsiveness to disturbances. This paper presents an adaptive time-stepping architecture for real-time planning with several advantageous properties. By dynamically adapting to the amount of time needed for a sample-based motion planner to make progress toward the goal, the technique is robust to the typically high variance exhibited by replanning queries. The technique is proven to be safe and asymptotically complete in a deterministic environment and a static objective. For unpredictably moving obstacles, the technique can be applied to keep the robot safe more reliably than reactive obstacle avoidance or fixed time-step replanning. It can also be applied in a contingency planning algorithm that achieves simultaneous safety-seeking and goal-seeking motion. These techniques generate responsive and safe motion in both simulated and real robots across a range of difficulties, including applications to bounded-acceleration pursuit-evasion, indoor navigation among moving obstacles, and aggressive collision-free teleoperation of an industrial robot arm.