High-level Planning for Multi-agent System using a Sampling-based method

Sammanfattning: One of the main focus of robotics is to integraterobotic tasks and motion planning, which has an increasedsignificance due to their growing number of application fieldsin transportation, navigation, warehouse management and muchmore. A crucial step towards this direction is to have robotsautomatically plan its trajectory to accomplish the given task.In this project a multi-layered approach was implemented toaccomplish it. Our framework consists of a discrete high-levelplanning layer that is designed for planning, and a continuouslow-level search layer that uses a sampling-based method for thetrajectory searching. The layers will interact with each otherduring the search for a solution. In order to coordinate formulti-agent system, velocity tuning is used to avoid collisions, anddifferent priority are assigned to each robot to avoid deadlocks.As a result, the framework trades off completeness for efficiency.The main aim of this project is to study and learn about high-level motion planning and multi-agent system, as an introductionto robotics and computer science.