In this work, we consider the problem of decentralized multi-robot target tracking and
obstacle avoidance in dynamic environments. Each robot executes a local motion planning …

Accurately tracking dynamic targets relies on robots accounting for uncertainties in their own
states to share information and maintain safety. The problem becomes even more …

Multi-robot collaboration for target tracking presents significant challenges in hazardous
environments, including addressing robot failures, dynamic priority changes, and other …

We address a decentralized control problem for a multi-agent network whose goal is to track
a moving multi-target system over a cluttered environment. Our problem is comprised of two …

This work presents a method for multi-robot coordination based on a novel distributed
nonlinear model predictive control (NMPC) formulation for trajectory optimization and its …

Multirobot motion planning and control has been investigated for decades and is still an
active research area due to the growing demand for both performance optimality and safety …

In this paper, we present a distributed model predictive control (MPC) strategy for path
following and formation control of multi-agent systems with collision avoidance guarantees …

Control barrier function (CBF) constraints provide a rigorous characterization of the space of
control inputs that ensure the satisfaction of state constraints, such as collision avoidance, at …

It is challenging to avoid obstacles safely and efficiently for multiple robots of different
shapes in distributed and communication-free scenarios, where robots do not communicate …

The problem of decentralized multi-robot target tracking asks for jointly selecting actions, eg,
motion primitives, for the robots to maximize target tracking performance with local …