Computational geometry: an introduction
Computational geometry: an introduction
Toward efficient trajectory planning: the path-velocity decomposition
International Journal of Robotics Research
Robotworld: a multiple robot vision guided assembly system
Proceedings of the 4th international symposium on Robotics Research
Automatic programming of behavior-based robots using reinforcement learning
Artificial Intelligence
Interaction and intelligent behavior
Interaction and intelligent behavior
Formation Planning and Control of UGVs with Trailers
Autonomous Robots
Cooperative Cleaners: A Study in Ant Robotics
International Journal of Robotics Research
Fuzzy motion control strategy for cooperation of multiple automated vehicles with passengers comfort
Automatica (Journal of IFAC)
Brief paper: Finite-time formation control for multi-agent systems
Automatica (Journal of IFAC)
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
A new hybrid navigation algorithm for mobile robots in environments with incomplete knowledge
Knowledge-Based Systems
Safe distributed motion coordination for second-order systems with different planning cycles
International Journal of Robotics Research
Automatica (Journal of IFAC)
A hybrid navigation strategy for multiple mobile robots
Robotics and Computer-Integrated Manufacturing
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This paper presents an approach for decentralized real-time motionplanning for multiple mobile robots operating in a common2-dimensional environment with unknown stationary obstacles. In ourmodel, a robot can see (sense) the surrounding objects. It knows itscurrent and its target‘s position, is able to distinguish a robotfrom an obstacle, and can assess the instantaneous motion of anotherrobot. Other than this, a robot has no knowledge about the scene orof the paths and objectives of other robots. There is no mutualcommunication among the robots; no constraints are imposed on thepaths or shapes of robots and obstacles. Each robot plans its pathtoward its target dynamically, based on its current position and thesensory feedback; only the translation component is considered forthe planning purposes. With this model, it is clear that no provablemotion planning strategy can be designed (a simple example with adead-lock is discussed); this naturally points to heuristicalgorithms. The suggested strategy is based on maze-searchingtechniques. Computer simulation results are provided thatdemonstrate good performance and a remarkable robustness of thealgorithm (meaning by this a virtual impossibility to create adead-lock in a “random” scene).