An overview on optimal flocking

LE Beaver, AA Malikopoulos - Annual Reviews in Control, 2021 - Elsevier
The decentralized aggregate motion of many individual robots is known as robotic flocking.
The study of robotic flocking has received considerable attention in the past twenty years. As …

Autotamp: Autoregressive task and motion planning with llms as translators and checkers

Y Chen, J Arkin, C Dawson, Y Zhang… - … on robotics and …, 2024 - ieeexplore.ieee.org
For effective human-robot interaction, robots need to understand, plan, and execute
complex, long-horizon tasks described by natural language. Recent advances in large …

[HTML][HTML] Reinforcement learning for swarm robotics: An overview of applications, algorithms and simulators

MA Blais, MA Akhloufi - Cognitive Robotics, 2023 - Elsevier
Robots such as drones, ground rovers, underwater vehicles and industrial robots have
increased in popularity in recent years. Many sectors have benefited from this by increasing …

How to train your neural control barrier function: Learning safety filters for complex input-constrained systems

O So, Z Serlin, M Mann, J Gonzales… - … on Robotics and …, 2024 - ieeexplore.ieee.org
Control barrier functions (CBFs) have become popular as a safety filter to guarantee the
safety of nonlinear dynamical systems for arbitrary inputs. However, it is difficult to construct …

Runtime assurance for safety-critical systems: An introduction to safety filtering approaches for complex control systems

KL Hobbs, ML Mote, MCL Abate… - IEEE Control …, 2023 - ieeexplore.ieee.org
More than three miles above the Arizona desert, an F-16 student pilot experienced a gravity-
induced loss of consciousness, passing out while turning at nearly 9Gs (nine times the force …

Learning scheduling policies for multi-robot coordination with graph attention networks

Z Wang, M Gombolay - IEEE Robotics and Automation Letters, 2020 - ieeexplore.ieee.org
Increasing interest in integrating advanced robotics within manufacturing has spurred a
renewed concentration in developing real-time scheduling solutions to coordinate human …

Adaptive bearing-only formation tracking control for nonholonomic multiagent systems

X Li, C Wen, X Fang, J Wang - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
In this article, we consider the formation tracking problem of nonholonomic multiagent
systems only using relative bearing measurements between the agents. Such a practical …

A resilient and energy-aware task allocation framework for heterogeneous multirobot systems

G Notomista, S Mayya, Y Emam… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
In the context of heterogeneous multirobot teams deployed for executing multiple tasks, this
article develops an energy-aware framework for allocating tasks to robots in an online …

Run time assured reinforcement learning for safe satellite docking

K Dunlap, M Mote, K Delsing, KL Hobbs - Journal of Aerospace …, 2023 - arc.aiaa.org
Reinforcement learning promises high performance in complex tasks as well as low online
storage and computation cost. However, the trial-and-error learning approach of …

ForzaETH Race Stack—Scaled Autonomous Head‐to‐Head Racing on Fully Commercial Off‐the‐Shelf Hardware

N Baumann, E Ghignone, J Kühne… - Journal of Field …, 2024 - Wiley Online Library
Autonomous racing in robotics combines high‐speed dynamics with the necessity for
reliability and real‐time decision‐making. While such racing pushes software and hardware …