Abstract: With the rapid advancement of mobile robot technology over the last decade, multi-
robot systems are now prevalent in the day-to-day operations of many businesses, such as
warehouse logistics, automated port, smart manufacturing, and search-and-rescue. These
systems leverage the joint capabilities of a team of mobile robots to achieve tasks that cannot
be done by any one of them, but at the cost of the additional complexity of efficiently
coordinating the motion of each robot. To address this challenge, this talk focuses on Multi-
Agent Path Finding (MAPF) problems. Traditionally, MAPF requires finding collision-free paths
for multiple agents from their respective initial locations to destinations while optimizing a single
criterion such as path length. This talk extends the conventional notion of MAPF and discusses
search-based path planning algorithms that can direct multiple agents to efficiently visit a large
number of intermediate target locations, and optimize multiple path criteria during the planning
process. Variants of these algorithms are also covered to further balance between runtime
efficiency and bounded sub-optimality of the computed solutions.