About Me

Discrete-time multi-agent pathfinding (MAPF) problems have been extensively studied, with conflict-based search (CBS) being a well-known optimal algorithm for solving classical MAPF instances, and Large Neighborhood Search being a fast alternative method to obtain a sub-optimal solution. In a continuous-time MAPF problem, conflicts can occur between agents traversing different edges, as well as between an agent waiting at a node and another agent moving along an edge. We considered all types of ...

In real-world multi-agent applications, unexpected conditions can break the assumptions made in path planning and degrade the effectiveness of path execution. This paper studies robust and effective execution of multi-agent path plans under uncertainty. To guarantee conflict-freeness and deadlock-freeness, we define a feasibility problem to check whether the remaining portion of a path plan can be successfully executed. We prove that the problem is NP-complete and propose a feasibility test algo ...

We study the multi-agent pickup and delivery problem with task deadlines, where a team of agents execute a batch of tasks with individual deadlines to maximize the number of tasks completed by their deadlines. Existing approaches to multi-agent pickup and delivery typically address task assignment and path planning separately. We take an integrated approach that assigns and plans one task at a time taking into account the agent states resulting from all the previous task assignments and path pla ...

Building operating systems are an emerging class of system software that provides services to applications running on commercial buildings. The current state-of-the-art requires applications to be trusted and carefully monitored due to a lack of authorization, access control, and execution isolation mechanisms in existing building operating systems. Proposed solutions do not adequately handle the complexity and scale of modern buildings, therefore impeding the adoption of applications that can e ...

Most prior work on multi-agent path finding and execution has assumed that time is discretized into timesteps and the agents move in grid maps with uniform action durations. However, in real-world multi-agent applications, agents of different shapes can move in arbitrary directions, and unforeseen failures and anomalies can cause unexpected delays of the agents. These delays are difficult to model and predict, and they can break the assumptions made in path planning and degrade the effectiveness ...