Chance Constrained Simultaneous Task Allocation and Path Planning for Multi-Robot Systems

Explore a comprehensive algorithmic approach for solving Simultaneous Task Allocation and Path Planning (STAPP) problems in multi-robot systems during this 1 hour and 28 minute lecture from VinAI. Delve into application scenarios such as parts transfer, mobility-on-demand, and search and rescue operations where robots must navigate to spatially distributed target destinations in open environments with uncontrolled mobile agents. Learn how to optimize team performance by assigning tasks to robots and planning collision-free paths while accounting for stochastic costs. Discover a novel two-dimensional geometric interpretation of the problem, enabling the development of a methodical one-parameter search algorithm for computing optimal solutions. Examine the formulation of STAPP problems as chance-constrained combinatorial optimization problems and understand the challenges in solving them. Gain insights into the scalability of this approach through computational experiments demonstrating its effectiveness with increasing numbers of robots and tasks.

Chance Constrained Simultaneous Task Allocation and Path Planning for Multi-Robot Systems