David Zahradka presents Robotics RG

Dear colleagues,
let me invite you to the next robotics RG, which takes place on Friday (3.12) at
9:00 in CIIRC JP:B-335. David Zahradka will present the following paper:

Z. Chen, J. Alonso-Mora, X. Bai, D. D. Harabor and P. J. Stuckey, "Integrated
Task
Assignment and Path Planning for Capacitated Multi-Agent Pickup and Delivery,"
in IEEE Robotics and Automation Letters, vol. 6, no. 3, pp. 5816-5823, July
2021

Paper link: https://ieeexplore.ieee.org/document/9410352

RG homepage: https://cw.fel.cvut.cz/wiki/courses/xp33rg2/start

Video call link: https://meet.google.com/jyu-vfim-kbc

Abstract:
Multi-agent Pickup and Delivery (MAPD) is a challenging industrial problem where
a team of robots is tasked with transporting a set of tasks, each from an
initial location and each to a specified target location. Appearing in the
context of automated warehouse logistics and automated mail sortation, MAPD
requires first deciding which robot is assigned what task (i.e., Task Assignment
or TA) followed by a subsequent coordination problem where each robot must be
assigned collision-free paths so as to successfully complete its assignment
(i.e., Multi-Agent Path Finding or MAPF). Leading methods in this area solve
MAPD sequentially: first assigning tasks, then assigning paths. In this work we
propose a new coupled method where task assignment choices are informed by
actual delivery costs instead of by lower-bound estimates. The main ingredients
of our approach are a marginal-cost assignment heuristic and a meta-heuristic
improvement strategy based on Large Neighbourhood Search. As a further
contribution, we also consider a variant of the MAPD problem where each robot
can carry multiple tasks instead of just one. Numerical simulations show that
our approach yields efficient and timely solutions and we report significant
improvement compared with other recent methods from the literature.