Collision-free Path Planning in Multi-vehicle Deployments – A Quantum Approach

A crucial factor that can severely limit the success and performance of Multi-Robot Systems (MRS) is the possibility of collisions among the robots in a deployment. The MRS deployment in real-world applications has increased almost exponentially in recent years. Thus, finding efficient and fast methods to identify collision-free paths for MRS environments becomes very important.A common objective in such applications is to generate a collision-free path for all the vehicles between two points and minimize the total distance covered while reaching the destination. Since these problems are known to be NP-hard (i.e., no classical algorithm can solve the problem in polynomial time), a heuristics-based approach is usually applied to obtain an acceptable solution.We derive a novel Quantum Alternating Operator Ansatz (QAOA) construction for collision-free path planning in MRS deployment. A heuristic approach such as the QAOA is well suited for combinatorial optimization problems that need to satisfy multiple hard constraints. We also derive the approximate resource estimates in terms of universal quantum gates for our QAOA constructions.