Multi-Agent Path Finding

Robot swarms and multi-robot systems are very popular and are used in various applications. In most of such applications, navigation to certain positions and path planning for several robots within an environment pose a challenge for algorithm design. Currently robots rely on purely reactive behavior resulting in sub-optimal paths. The long term goal of our research is to extend the capabilities of the agents to plan future actions, taking into account the intend of their neighbors, to obtain more efficient behaviors. In order to optimally navigate within a moving robotic swarm, we need a framework for planning, evaluating and executing trajectories in a very dynamic environment. In the following paper, we propose a model to represent trajectories for multiple robots within a swarm, respecting the kinematic constraints of the robots given by a specific vehicle model.

  • Sebastian Mai and Sanaz Mostaghim 
  • Modelling Pathfinding for Swarm Robotics
  • In: Dorigo M. et al. (eds) Swarm Intelligence. ANTS 2020. Lecture Notes in Computer Science, vol 12421. Springer, Cham. 2020. https://doi.org/10.1007/978-3-030-60376-2_15

 

  

 

 

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