Search Results - Machine Learning for Robot Control

Orbit: A Unified Simulation Framework for Interactive Robot Learning Environments by Mittal, Mayank, Yu, Calvin, Yu, Qinxi, Liu, Jingzhou, Rudin, Nikita, Hoeller, David, Yuan, Jia Lin, Singh, Ritvik, Guo, Yunrong, Mazhar, Hammad, Mandlekar, Ajay, Babich, Buck, State, Gavriel, Hutter, Marco, Garg, Animesh

“…We present Orbit , a unified and modular framework for robot learning powered by Nvidia Isaac Sim…”
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CALVIN: A Benchmark for Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation Tasks by Mees, Oier, Hermann, Lukas, Rosete-Beas, Erick, Burgard, Wolfram Burgard

“…General-purpose robots coexisting with humans in their environment must learn to relate human language to their perceptions and actions to be useful in a range of daily tasks…”
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What Matters in Language Conditioned Robotic Imitation Learning Over Unstructured Data by Mees, Oier, Hermann, Lukas, Burgard, Wolfram

“…A long-standing goal in robotics is to build robots that can perform a wide range of daily tasks from perceptions obtained with their onboard sensors and specified only via natural language…”
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A Lifelong Learning Approach to Mobile Robot Navigation by Liu, Bo, Xiao, Xuesu, Stone, Peter

“…This letter presents a self-improving lifelong learning framework for a mobile robot navigating in different environments…”
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CPG-RL: Learning Central Pattern Generators for Quadruped Locomotion by Bellegarda, Guillaume, Ijspeert, Auke

“…In this letter, we present a method for integrating central pattern generators (CPGs), i.e. systems of coupled oscillators, into the deep reinforcement learning…”
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Safe-Control-Gym: A Unified Benchmark Suite for Safe Learning-Based Control and Reinforcement Learning in Robotics by Yuan, Zhaocong, Hall, Adam W., Zhou, Siqi, Brunke, Lukas, Greeff, Melissa, Panerati, Jacopo, Schoellig, Angela P.

“…In recent years, both reinforcement learning and learning-based control-as well as the study of their safety , which is crucial for deployment in real-world robots-have gained significant traction…”
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Real-Time Neural MPC: Deep Learning Model Predictive Control for Quadrotors and Agile Robotic Platforms by Salzmann, Tim, Kaufmann, Elia, Arrizabalaga, Jon, Pavone, Marco, Scaramuzza, Davide, Ryll, Markus

“… In contrast to such simple models, machine learning approaches, specifically neural networks, have been shown to accurately model even complex dynamic effects, but their large computational…”
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Learning-Based Balance Control of Wheel-Legged Robots by Cui, Leilei, Wang, Shuai, Zhang, Jingfan, Zhang, Dongsheng, Lai, Jie, Zheng, Yu, Zhang, Zhengyou, Jiang, Zhong-Ping

“…) to derive a learning-based solution to adaptive optimal control. It is shown that suboptimal controllers can be learned directly from input-state data collected along the trajectories of the robot…”
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Model-Based Meta-Reinforcement Learning for Flight With Suspended Payloads by Belkhale, Suneel, Li, Rachel, Kahn, Gregory, McAllister, Rowan, Calandra, Roberto, Levine, Sergey

“… These changes can lead to suboptimal flight performance or even catastrophic failure. Although adaptive control and learning-based methods can in principle adapt to changes…”
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Learning Variable Impedance Control via Inverse Reinforcement Learning for Force-Related Tasks by Zhang, Xiang, Sun, Liting, Kuang, Zhian, Tomizuka, Masayoshi

“…Many manipulation tasks require robots to interact with unknown environments. In such applications, the ability to adapt the impedance according to different task phases and environment constraints is crucial for safety and performance…”
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KNODE-MPC: A Knowledge-Based Data-Driven Predictive Control Framework for Aerial Robots by Chee, Kong Yao, Jiahao, Tom Z., Hsieh, M. Ani

“…In this letter, we consider the problem of deriving and incorporating accurate dynamic models for model predictive control (MPC…”
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Data-driven predictive control of nonholonomic robots based on a bilinear Koopman realization: Data does not replace geometry by Rosenfelder, Mario, Bold, Lea, Eschmann, Hannes, Eberhard, Peter, Worthmann, Karl, Ebel, Henrik

“…Advances in machine learning and the growing trend towards effortless data generation in real-world systems have led to an increasing interest for data-inferred models and data-based control in robotics…”
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Reinforcement Learning With Evolutionary Trajectory Generator: A General Approach for Quadrupedal Locomotion by Shi, Haojie, Zhou, Bo, Zeng, Hongsheng, Wang, Fan, Dong, Yueqiang, Li, Jiangyong, Wang, Kang, Tian, Hao, Meng, Max Q.-H.

“…Recently reinforcement learning (RL) has emerged as a promising approach for quadrupedal locomotion, which can save the manual effort in conventional approaches such as designing skill-specific controllers…”
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Deep Koopman Operator With Control for Nonlinear Systems by Shi, Haojie, Meng, Max Q.-H.

“…Recently Koopman operator has become a promising data-driven tool to facilitate real-time control for unknown nonlinear systems…”
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Learning Inverse Kinodynamics for Accurate High-Speed Off-Road Navigation on Unstructured Terrain by Xiao, Xuesu, Biswas, Joydeep, Stone, Peter

“…This letter presents a learning-based approach to consider the effect of unobservable world states in kinodynamic motion planning in order to enable accurate high-speed off-road navigation on unstructured terrain…”
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OmniDrones: An Efficient and Flexible Platform for Reinforcement Learning in Drone Control by Xu, Botian, Gao, Feng, Yu, Chao, Zhang, Ruize, Wu, Yi, Wang, Yu

“…In this letter, we introduce OmniDrones , an efficient and flexible platform tailored for reinforcement learning in drone control, built on Nvidia's Omniverse Isaac Sim…”
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Learning Robust and Agile Legged Locomotion Using Adversarial Motion Priors by Wu, Jinze, Xin, Guiyang, Qi, Chenkun, Xue, Yufei

“…Developing both robust and agile locomotion skills for legged robots is non-trivial…”
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LaND: Learning to Navigate From Disengagements by Kahn, Gregory, Abbeel, Pieter, Levine, Sergey

“… However, we believe that these disengagements not only show where the system fails, which is useful for troubleshooting, but also provide a direct learning signal by which the robot can learn to navigate…”
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Learning Free Gait Transition for Quadruped Robots Via Phase-Guided Controller by Shao, Yecheng, Jin, Yongbin, Liu, Xianwei, He, Weiyan, Wang, Hongtao, Yang, Wei

“… Reinforcement learning has become a powerful tool to formulate controllers for legged robots. Learning multiple gaits and transitions, nevertheless, is related to the multi-task learning problems…”
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Toward Agile Maneuvers in Highly Constrained Spaces: Learning From Hallucination by Xiao, Xuesu, Liu, Bo, Warnell, Garrett, Stone, Peter

“…, where the robot needs to engage in agile maneuvers to squeeze between obstacles. Recent machine learning techniques have the potential to address this shortcoming…”
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