Title :
Planning Paths for Package Delivery in Heterogeneous Multirobot Teams
Author :
Mathew, Neil ; Smith, Stephen L. ; Waslander, Steven L.
Author_Institution :
Dept. of Mech. & Mechatron. Eng., Univ. of Waterloo, Waterloo, ON, Canada
Abstract :
This paper addresses the task scheduling and path planning problem for a team of cooperating vehicles performing autonomous deliveries in urban environments. The cooperating team comprises two vehicles with complementary capabilities, a truck restricted to travel along a street network, and a quadrotor micro-aerial vehicle of capacity one that can be deployed from the truck to perform deliveries. The problem is formulated as an optimal path planning problem on a graph and the goal is to find the shortest cooperative route enabling the quadrotor to deliver items at all requested locations. The problem is shown to be NP-hard. A solution is then proposed using a novel reduction to the Generalized Traveling Salesman Problem, for which well-established heuristic solvers exist. The heterogeneous delivery problem contains as a special case the problem of scheduling deliveries from multiple static warehouses. We propose two additional algorithms, based on enumeration and a reduction to the traveling salesman problem, for this special case. Simulation results compare the performance of the presented algorithms and demonstrate examples of delivery route computations over real urban street maps.
Keywords :
autonomous aerial vehicles; computational complexity; goods distribution; industrial robots; multi-robot systems; path planning; road vehicles; NP-hard problem; autonomous delivery; cooperating vehicles; generalized traveling salesman problem; heterogeneous delivery problem; heterogeneous multirobot teams; package delivery; path planning; quadrotor microaerial vehicle; static warehouses; task scheduling; truck; Multi-robot systems; Path planning; Traveling salesman problems; Unmanned aerial vehicles; Urban areas; Generalized traveling salesman problem; optimal path planning; unmanned aerial vehicles; urban delivery;
Journal_Title :
Automation Science and Engineering, IEEE Transactions on
DOI :
10.1109/TASE.2015.2461213