Autonomous robotic systems are complex, hybrid, and often safety critical; this makes their
formal specification and verification uniquely challenging. Though commonly used, testing …

The control of a multiple unmanned aerial vehicle (UAV) system is popular and attracting a
lot of attentions. This is motivated by many practical civil and commercial UAV applications …

In the multi-agent pathfinding problem (MAPF) we are given a set of agents each with
respective start and goal positions. The task is to find paths for all agents while avoiding …

The task in the multi-agent path finding problem (MAPF) is to find paths for multiple agents,
each with a different start and goal position, such that agents do not collide. A successful …

We review a range of techniques related to navigation of unmanned vehicles through
unknown environments with obstacles, especially those that rigorously ensure collision …

Multi-agent pathfinding (MAPF) is an area of expanding research interest. At the core of this
research area, numerous diverse search-based techniques were developed in the past 6 …

This self-contained introduction to the distributed control of robotic networks offers a
distinctive blend of computer science and control theory. The book presents a broad set of …

We address the problem of optimal pathfinding for multiple agents. Given a start state and a
goal state for each of the agents, the task is to find minimal paths for the different agents …

We propose a novel approach for optimal trajectory tracking for unmanned aerial vehicles
(UAV), using a linear model predictive controller (MPC) in combination with non-linear state …

The presence of uncertainty in a system description has always been a critical issue in
control. The main objective of Randomized Algorithms for Analysis and Control of Uncertain …