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检索条件"主题词=deep learning in robotics and automation"
221 条 记 录,以下是21-30 订阅
排序:
DRL-VO: learning to Navigate Through Crowded Dynamic Scenes Using Velocity Obstacles
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IEEE TRANSACTIONS ON robotics 2023年 第4期39卷 2700-2719页
作者: Xie, Zhanteng Dames, Philip Temple Univ Dept Mech Engn Philadelphia PA 19122 USA
This article proposes a novel learning-based control policy with strong generalizability to new environments that enables a mobile robot to navigate autonomously through spaces filled with both static obstacles and de... 详细信息
来源: 评论
Object Detection Using Sim2Real Domain Randomization for Robotic Applications
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IEEE TRANSACTIONS ON robotics 2023年 第2期39卷 1225-1243页
作者: Horvath, Daniel Erdos, Gabor Istenes, Zoltan Horvath, Tomas Foldi, Sandor Eotvos Lorand Res Network Ctr Excellence Prod Informat & Control Inst Comp Sci & Control H-1111 Budapest Hungary Eotvos Lorand Univ CoLocat Ctr Acad & Ind Cooperat H-1117 Budapest Hungary Budapest Univ Technol & Econ Dept Mfg Sci & Engn H-1111 Budapest Hungary Eotvos Lorand Univ Dept Data Sci & Engn H-1117 Budapest Hungary Pavol Jozef Safar Univ Fac Sci Inst Comp Sci Kosice 04001 Slovakia
Robots working in unstructured environments must be capable of sensing and interpreting their surroundings. One of the main obstacles of deep-learning-based models in the field of robotics is the lack of domain-specif... 详细信息
来源: 评论
Safe Control With Learned Certificates: A Survey of Neural Lyapunov, Barrier, and Contraction Methods for robotics and Control
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IEEE TRANSACTIONS ON robotics 2023年 第3期39卷 1749-1767页
作者: Dawson, Charles Gao, Sicun Fan, Chuchu MIT Dept Aeronaut & Astronaut Cambridge MA 02139 USA Univ Calif San Diego Dept Comp Sci & Engn La Jolla CA 92093 USA
learning-enabled control systems have demonstrated impressive empirical performance on challenging control problems in robotics, but this performance comes at the cost of reduced transparency and lack of guarantees on... 详细信息
来源: 评论
deep learning Reactive Robotic Grasping With a Versatile Vacuum Gripper
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IEEE TRANSACTIONS ON robotics 2023年 第2期39卷 1244-1259页
作者: Zhang, Hui Peeters, Jef Demeester, Eric Kellens, Karel ACRO Res Grp Dept Mech Engn B-3590 Diepenbeek Belgium LCE Res Grp Dept Mech Engn B-3001 Heverlee Belgium Katholieke Univ Leuven Flanders Make VCCM Core Lab B-3000 Leuven Belgium
In this article, a six-step approach is proposed to simu-late the grasp and evaluate the grasp quality for a versatile vacuum gripper by tracking the deformation and force-torque wrench of the gripping pad. Over 100 K... 详细信息
来源: 评论
deep learning Approaches to Grasp Synthesis: A Review
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IEEE TRANSACTIONS ON robotics 2023年 第5期39卷 3994-4015页
作者: Newbury, Rhys Gu, Morris Chumbley, Lachlan Mousavian, Arsalan Eppner, Clemens Leitner, Jurgen Bohg, Jeannette Morales, Antonio Asfour, Tamim Kragic, Danica Fox, Dieter Cosgun, Akansel Monash Univ Clayton Vic 3800 Australia Australian Natl Univ Canberra ACT 2601 Australia NVIDIA Corp Seattle WA 98105 USA LYRO Robot Pty Ltd Clayton Vic 3168 Australia Stanford Univ Stanford CA 94305 USA Jaume I Univ Castellon De La Plana 12071 Spain Karlsruhe Inst Technol D-76131 Karlsruhe Germany KTH Royal Inst Technol S-10044 Stockholm Sweden Univ Washington Seattle WA 98195 USA Deakin Univ Burwood Vic 3125 Australia
Grasping is the process of picking up an object by applying forces and torques at a set of contacts. Recent advances in deep learning methods have allowed rapid progress in robotic object grasping. In this systematic ... 详细信息
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TACTO: A Fast, Flexible, and Open-Source Simulator for High-Resolution Vision-Based Tactile Sensors
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IEEE robotics AND automation LETTERS 2022年 第2期7卷 3930-3937页
作者: Wang, Shaoxiong Lambeta, Mike Chou, Po-Wei Calandra, Roberto Meta AI Menlo Pk CA 94025 USA MIT Cambridge MA 02139 USA
Simulators perform an important role in prototyping, debugging, and benchmarking new advances in robotics and learning for control. Although many physics engines exist, some aspects of the real world are harder than o... 详细信息
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RLOC: Terrain-Aware Legged Locomotion Using Reinforcement learning and Optimal Control
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IEEE TRANSACTIONS ON robotics 2022年 第5期38卷 2908-2927页
作者: Gangapurwala, Siddhant Geisert, Mathieu Orsolino, Romeo Fallon, Maurice Havoutis, Ioannis Univ Oxford Oxford Robot Inst Dynam Robots Syst Grp Oxford OX2 6NN England
We present a unified model-based and data-driven approach for quadrupedal planning and control to achieve dynamic locomotion over uneven terrain. We utilize on-board proprioceptive and exteroceptive feedback to map se... 详细信息
来源: 评论
Constrained Motion Planning Networks X
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IEEE TRANSACTIONS ON robotics 2022年 第2期38卷 868-886页
作者: Qureshi, Ahmed Hussain Dong, Jiangeng Baig, Asfiya Yip, Michael C. Univ Calif San Diego La Jolla CA 92093 USA Univ Calif San Diego Elect & Comp Engn La Jolla CA 92093 USA
Constrained motion planning is a challenging field of research, aiming for computationally efficient methods that can find a collision-free path on the constraint manifolds between a given start and goal configuration... 详细信息
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Integrating contrastive learning with dynamic models for reinforcement learning from images
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NEUROCOMPUTING 2022年 第0期476卷 102-114页
作者: You, Bang Arenz, Oleg Chen, Youping Peters, Jan Huazhong Univ Sci & Technol Sch Mech Sci & Engn Wuhan 430074 Peoples R China Tech Univ Darmstadt Intelligent Autonomous Syst Lab D-64289 Darmstadt Germany
Recent methods for reinforcement learning from images use auxiliary tasks to learn image features that are used by the agent's policy or Q-function. In particular, methods based on contrastive learning that induce... 详细信息
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HGLP: Hierarchical Solver for Combined Task Assignment and Path Finding  35
HGLP: Hierarchical Solver for Combined Task Assignment and P...
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35th Chinese Control and Decision Conference (CCDC)
作者: Gao, Jianqi Ye, Zhaohui Li, Xinyi Li, Yanjie Harbin Inst Technol Shenzhen Sch Mech Engn & Automat Shenzhen Peoples R China
Intelligent warehouse based on the multi-robot system significantly improves logistics efficiency. Completing orders usually includes order task assignment and multi-robot path planning. These two processes influence ... 详细信息
来源: 评论