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Related papers: Co-Evolution of Multi-Robot Controllers and Task C…

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Future crewed missions to the Moon will face significant environmental and operational challenges, posing risks to the safety and performance of astronauts navigating its inhospitable surface. Whilst head-up displays (HUDs) have proven…

Autonomous multi-robot optical inspection systems are increasingly applied for obtaining inline measurements in process monitoring and quality control. Numerous methods for path planning and robotic coordination have been developed for…

Robotics · Computer Science 2021-06-16 Yinhua Liu , Wenzheng Zhao , Tim Lutz , Xiaowei Yue

Multi-Agent Task Assignment and Planning (MATP) has attracted growing attention but remains challenging in terms of scalability, spatial reasoning, and adaptability in obstacle-rich environments. To address these challenges, we propose OATH…

Robotics · Computer Science 2026-04-09 Nan Li , Jiming Ren , Haris Miller , Samuel Coogan , Karen M. Feigh , Ye Zhao

The growing deployment of human-robot collaborative processes in several industrial applications, such as handling, welding, and assembly, unfolds the pursuit of systems which are able to manage large heterogeneous teams and, at the same…

Robotics · Computer Science 2023-09-26 Edoardo Lamon , Fabio Fusaro , Elena De Momi , Arash Ajoudani

Autonomous Underwater Vehicles (AUVs) need to operate for days without human intervention and thus must be able to do efficient and reliable task planning. Unfortunately, efficient task planning requires deliberately abstract domain models…

Exploration of unknown, unstructured environments, such as in search and rescue, cave exploration, and planetary missions,presents significant challenges due to their unpredictable nature. This unpredictability can lead to inefficient path…

Robotics · Computer Science 2024-10-08 Riana Gagnon Souleiman , Vivek Shankar Varadharajan , Giovanni Beltrame

We address multi-robot geometric task-and-motion planning (MR-GTAMP) problems in synchronous, monotone setups. The goal of the MR-GTAMP problem is to move objects with multiple robots to goal regions in the presence of other movable…

Artificial intelligence has undergone immense growth and maturation in recent years, though autonomous systems have traditionally struggled when fielded in diverse and previously unknown environments. DARPA is seeking to change that with…

Autonomy for robots interacting with sand will enable a wide range of beneficial behaviors, from earth moving for construction and farming vehicles to navigating rough terrain for Mars rovers. The goal of this work is to shape sand into…

Robotics · Computer Science 2019-08-08 Wooshik Kim , Catherine Pavlov , Aaron M. Johnson

Deploying robotic missions can be challenging due to the complexity of controlling robots with multiple degrees of freedom, fusing diverse sensory inputs, and managing communication delays and interferences. In nuclear inspection, robots…

Dynamic task allocation is an essential requirement for multi-robot systems operating in unknown dynamic environments. It allows robots to change their behavior in response to environmental changes or actions of other robots in order to…

Robotics · Computer Science 2007-05-23 Kristina Lerman , Chris Jones , Aram Galstyan , Maja J Mataric

Human-Robot Collaboration (HRC) has evolved into a highly promising issue owing to the latest breakthroughs in Artificial Intelligence (AI) and Human-Robot Interaction (HRI), among other reasons. This emerging growth increases the need to…

Robotics · Computer Science 2024-10-02 Oscar Gil Viyuela , Alberto Sanfeliu

Legged robots are promising candidates for exploring challenging areas on low-gravity bodies such as the Moon, Mars, or asteroids, thanks to their advanced mobility on unstructured terrain. However, as planetary robots' power and thermal…

Robotics · Computer Science 2025-11-17 Philip Arm , Oliver Fischer , Joseph Church , Adrian Fuhrer , Hendrik Kolvenbach , Marco Hutter

One simplifying assumption in existing and well-performing task allocation methods is that the robots are single-tasking: each robot operates on a single task at any given time. While this assumption is harmless to make in some situations,…

Robotics · Computer Science 2026-03-10 Winston Smith , Yu Zhang

Space exploration missions have seen use of increasingly sophisticated robotic systems with ever more autonomy. Deep learning promises to take this even a step further, and has applications for high-level tasks, like path planning, as well…

Machine Learning · Computer Science 2019-09-16 Tamir Blum , William Jones , Kazuya Yoshida

This paper presents a novel framework for automatically learning complete Stack-of-Tasks (SoT) controllers for redundant robotic systems, including task priorities, activation logic, and control parameters. Unlike classical SoT…

Robotics · Computer Science 2025-12-24 Alessandro Adami , Aris Synodinos , Matteo Iovino , Ruggero Carli , Pietro Falco

This work addresses the coordination problem of multiple robots with the goal of finding specific hazardous targets in an unknown area and dealing with them cooperatively. The desired behaviour for the robotic system entails multiple…

Robotics · Computer Science 2019-03-29 Nunzia Palmieri , Xin-She Yang , Floriano De Rango , Amilcare Francesco Santamaria

Lunar exploration has become a key focus, driving scientific and technological advances. Ongoing missions are deploying rovers to the surface of the Moon, targeting the far side and south pole. However, these terrains pose challenges,…

While much research explores improving robot capabilities, there is a deficit in researching how robots are expected to perform tasks safely, especially in high-risk problem domains. Robots must earn the trust of human operators in order to…

In this paper we consider the problem of coordinating robotic systems with different kinematics, sensing and vision capabilities to achieve certain mission goals. An approach that makes use of a heterogeneous team of agents has several…

Robotics · Computer Science 2015-09-04 Nicola Bezzo , Joshua P. Hecker , Karl Stolleis , Melanie E. Moses , Rafael Fierro