Results 11 to 20 of about 42,816 (266)
From Learning to Relearning: A Framework for Diminishing Bias in Social Robot Navigation
Frontiers in Robotics and AI, 2021 The exponentially increasing advances in robotics and machine learning are facilitating the transition of robots from being confined to controlled industrial spaces to performing novel everyday tasks in domestic and urban environments.
Juana Valeria Hurtado +2 more
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Motion Generation Using Bilateral Control-Based Imitation Learning With Autoregressive Learning
IEEE Access, 2021 Imitation learning has been studied as an efficient and high-performance method to generate robot motion. Specifically, bilateral control-based imitation learning has been proposed as a method of realizing fast motion.
Ayumu Sasagawa +2 more
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Learning Navigation Skills for Legged Robots with Learned Robot Embeddings [PDF]
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021 Recent work has shown results on learning navigation policies for idealized cylinder agents in simulation and transferring them to real wheeled robots. Deploying such navigation policies on legged robots can be challenging due to their complex dynamics, and the large dynamical difference between cylinder agents and legged systems.
Joanne Truong +6 more
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Zero-shot model-free learning of periodic movements for a bio-inspired soft-robotic arm
Frontiers in Robotics and AI, 2023 In recent years, soft robots gain increasing attention as a result of their compliance when operating in unstructured environments, and their flexibility that ensures safety when interacting with humans.
Paris Oikonomou +4 more
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Robot Learning With Crash Constraints [PDF]
IEEE Robotics and Automation Letters, 2021 In the past decade, numerous machine learning algorithms have been shown to successfully learn optimal policies to control real robotic systems. However, it is common to encounter failing behaviors as the learning loop progresses. Specifically, in robot applications where failing is undesired but not catastrophic, many algorithms struggle with ...
Alonso Marco +5 more
openaire +3 more sources
Frontiers in Robotics and AI, 2023 Long-horizon task planning is essential for the development of intelligent assistive and service robots. In this work, we investigate the applicability of a smaller class of large language models (LLMs), specifically GPT-2, in robotic task planning by ...
Georgia Chalvatzaki +8 more
doaj +1 more source
Robotics, 2023 This work proposes a Learning by Demonstration framework based on Dynamic Movement Primitives (DMPs) that could be effectively adopted to plan complex activities in robotics such as the ones to be performed in agricultural domains and avoid orientation ...
Clemente Lauretti +3 more
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Compound Heuristic Information Guided Policy Improvement for Robot Motor Skill Acquisition
Applied Sciences, 2020 Discovering the implicit pattern and using it as heuristic information to guide the policy search is one of the core factors to speed up the procedure of robot motor skill acquisition.
Jian Fu +4 more
doaj +1 more source
Knowledge driven indoor object‐goal navigation aid for visually impaired people
Cognitive Computation and Systems, 2022 Aiming to help improve quality of life of the visually impaired people, this paper presents a novel wearable aid in the shape of a helmet for helping them find objects in indoor scenes.
Xuan Hou +3 more
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