Results 31 to 40 of about 184,367 (278)
Sensors, 2020 The coexistence of robots and humans in shared physical and social spaces is expected to increase. A key enabler of high-quality interaction is a mutual understanding of each other’s actions and intentions.
Jessica Lindblom, Beatrice Alenljung
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Q-CP: Learning Action Values for Cooperative Planning [PDF]
, 2018 Research on multi-robot systems has demonstrated promising results in manifold applications and domains. Still, efficiently learning an effective robot behaviors is very difficult, due to unstructured scenarios, high uncertainties, and large state ...
Capobianco, Roberto +2 more
core +2 more sources
Multi-Agent Action Graph Based Task Allocation and Path Planning Considering Changes in Environment
IEEE Access, 2023 Task allocation and path planning considering changes in the mobility of robots in the environment allows the robots to efficiently execute tasks with smaller travel times.
Takuma Okubo, Masaki Takahashi
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Behavior trees in action: a study of robotics applications [PDF]
Proceedings of the 13th ACM SIGPLAN International Conference on Software Language Engineering, 2020 14 pages, 5 figures, 13rd ACM SIGPLAN International Conference on Software Language Engineering (SLE) (SLE 2020)
Razan Ghzouli +4 more
openaire +4 more sources
EEG theta and Mu oscillations during perception of human and robot actions. [PDF]
, 2013 The perception of others' actions supports important skills such as communication, intention understanding, and empathy. Are mechanisms of action processing in the human brain specifically tuned to process biological agents?
Ishiguro, Hiroshi +4 more
core +2 more sources
Special Issue on Intelligent Robots
Robotics, 2013 The research on intelligent robots will produce robots that are able to operate in everyday life environments, to adapt their program according to environment changes, and to cooperate with other team members and humans.
Genci Capi
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Sensing and Navigation for Multiple Mobile Robots Based on Deep Q-Network
Remote Sensing, 2023 In this paper, a novel DRL algorithm based on a DQN is proposed for multiple mobile robots to find optimized paths. The multiple robots’ states are the inputs of the DQN. The DQN estimates the Q-value of the agents’ actions.
Yanyan Dai, Seokho Yang, Kidong Lee
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Learning for Multi-robot Cooperation in Partially Observable Stochastic Environments with Macro-actions [PDF]
, 2017 This paper presents a data-driven approach for multi-robot coordination in partially-observable domains based on Decentralized Partially Observable Markov Decision Processes (Dec-POMDPs) and macro-actions (MAs). Dec-POMDPs provide a general framework for
Amato, Christopher +4 more
core +2 more sources
An Open-Source Simulator for Cognitive Robotics Research: The Prototype of the iCub Humanoid Robot Simulator [PDF]
, 2008 This paper presents the prototype of a new computer simulator for the humanoid robot iCub. The iCub is a new open-source humanoid robot developed as a result of the “RobotCub” project, a collaborative European project aiming at developing a new open ...
Cangelosi, Angelo +5 more
core +3 more sources
SA-Net: Deep Neural Network for Robot Trajectory Recognition from RGB-D Streams
, 2020 Learning from demonstration (LfD) and imitation learning offer new paradigms for transferring task behavior to robots. A class of methods that enable such online learning require the robot to observe the task being performed and decompose the sensed ...
Asali, Ehsan +3 more
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