Review of reinforcement learning for robotic gras**: Analysis and recommendations

H Sekkat, O Moutik, L Ourabah, B ElKari… - Statistics, Optimization …, 2024 - iapress.org
This review paper provides a comprehensive analysis of over 100 research papers focused
on the challenges of robotic gras** and the effectiveness of various machine learning …

Deep-reinforcement-learning-based path planning for industrial robots using distance sensors as observation

T Bhuiyan, L Kästner, Y Hu… - … on Control and …, 2023 - ieeexplore.ieee.org
Traditionally, collision-free path planning for industrial robots is realized by sampling-based
algorithms such as RRT (Rapidly-exploring Random Tree), PRM (Probabilistic Roadmap) …

Details make a difference: Object state-sensitive neurorobotic task planning

X Sun, X Zhao, JH Lee, W Lu, M Kerzel… - … Conference on Artificial …, 2024 - Springer
The state of an object reflects its current status or condition and is important for a robot's task
planning and manipulation. However, detecting an object's state and generating a state …

Model mediated teleoperation with a hand-arm exoskeleton in long time delays using reinforcement learning

H Beik-Mohammadi, M Kerzel… - 2020 29th IEEE …, 2020 - ieeexplore.ieee.org
Telerobotic systems must adapt to new environmental conditions and deal with high
uncertainty caused by long-time delays. As one of the best alternatives to human-level …

Multi-vehicle mixed-reality reinforcement learning for autonomous multi-lane driving

R Mitchell, J Fletcher, J Panerati, A Prorok - ar** and Manipulation
Z Deng - 2019 - ediss.sub.uni-hamburg.de
Dexterous gras** and manipulation of objects are fundamental abilities for robots. Our aim
is to endow robots with human-like gras** and manipulation capabilities. Four issues are …

Task-Based Feature Learning and Enhancement for Bandwidth-Limited Applications

JA White - 2022 - figshare.swinburne.edu.au
This research introduces an entirely new framework for vision processing that learns task-
based visual features and enhances them in images to guide human action in vision-based …

Adaptive Model Mediated Control Using Reinforcement Learning

H Beik-Mohammadi - 2020 - elib.dlr.de
Due to similarities in learning techniques, Reinforcement Learning (RL) is the closest
alternative to human-level intelligence. Teleoperation systems using RL can adapt to new …

[HTML][HTML] 一种基于功用性图的目标推抓技能自监督学**方法

吴培良, 刘瑞军, 毛秉毅, 史浩洋, 陈雯柏, 高国伟 - 机器人, 2022 - html.rhhz.net
提出了一种基于功用性图的目标推抓技能自监督学**方法. 首先, 给出了杂乱环境下面向目标推
抓任务的机器人技能自监督学**问题描述, 将工作空间中机器人推抓操作的决策过程定义为一个 …