2,758 research outputs found
Robots learn to behave: improving human-robot collaboration in flexible manufacturing applications
L'abstract è presente nell'allegato / the abstract is in the attachmen
Safe navigation and human-robot interaction in assistant robotic applications
L'abstract è presente nell'allegato / the abstract is in the attachmen
Role Engine Implementation for a Continuous and Collaborative Multi-Robot System
In situations involving teams of diverse robots, assigning appropriate roles
to each robot and evaluating their performance is crucial. These roles define
the specific characteristics of a robot within a given context. The stream
actions exhibited by a robot based on its assigned role are referred to as the
process role. Our research addresses the depiction of process roles using a
multivariate probabilistic function. The main aim of this study is to develop a
role engine for collaborative multi-robot systems and optimize the behavior of
the robots. The role engine is designed to assign suitable roles to each robot,
generate approximately optimal process roles, update them on time, and identify
instances of robot malfunction or trigger replanning when necessary. The
environment considered is dynamic, involving obstacles and other agents. The
role engine operates hybrid, with central initiation and decentralized action,
and assigns unlabeled roles to agents. We employ the Gaussian Process (GP)
inference method to optimize process roles based on local constraints and
constraints related to other agents. Furthermore, we propose an innovative
approach that utilizes the environment's skeleton to address initialization and
feasibility evaluation challenges. We successfully demonstrated the proposed
approach's feasibility, and efficiency through simulation studies and
real-world experiments involving diverse mobile robots.Comment: 10 pages, 18 figures, summited in IEEE Transactions on Systems, Man
and Cybernetics(T-SMC
Multi-Robot Systems: Challenges, Trends and Applications
This book is a printed edition of the Special Issue entitled “Multi-Robot Systems: Challenges, Trends, and Applications” that was published in Applied Sciences. This Special Issue collected seventeen high-quality papers that discuss the main challenges of multi-robot systems, present the trends to address these issues, and report various relevant applications. Some of the topics addressed by these papers are robot swarms, mission planning, robot teaming, machine learning, immersive technologies, search and rescue, and social robotics
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