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Transic: Sim-to-real policy transfer by learning from online correction
Automatic environment sha** is the next frontier in rl
Y Park, GB Margolis, P Agrawal - ar** and
challenging area in embodied AI. It is crucial for advancing next-generation intelligent robots …
challenging area in embodied AI. It is crucial for advancing next-generation intelligent robots …
[PDF][PDF] Actor-Critic Model Predictive Control: Differentiable Optimization meets Reinforcement Learning
An open research question in robotics is how to combine the benefits of model-free
reinforcement learning (RL)—known for its strong task performance and flexibility in …
reinforcement learning (RL)—known for its strong task performance and flexibility in …
[PDF][PDF] Limt: Language-informed multi-task visual world models
Most recent successes in robot reinforcement learning involve learning a specialized single-
task agent. However, robots capable of performing multiple tasks can be much more …
task agent. However, robots capable of performing multiple tasks can be much more …
Student-Informed Teacher Training
Imitation learning with a privileged teacher has proven effective for learning complex control
behaviors from high-dimensional inputs, such as images. In this framework, a teacher is …
behaviors from high-dimensional inputs, such as images. In this framework, a teacher is …
Integrating DeepRL with Robust Low-Level Control in Robotic Manipulators for Non-Repetitive Reaching Tasks
In robotics, contemporary strategies are learning-based, characterized by a complex black-
box nature and a lack of interpretability, which may pose challenges in ensuring stability and …
box nature and a lack of interpretability, which may pose challenges in ensuring stability and …
Evolving Control: Evolved High Frequency Control for Continuous Control Tasks
High-frequency control in continuous action and state spaces is essential for practical
applications in the physical world. Directly learning end-to-end high-frequency control …
applications in the physical world. Directly learning end-to-end high-frequency control …
[HTML][HTML] Curriculum Design and Sim2Real Transfer for Reinforcement Learning in Robotic Dual-Arm Assembly
K Wrede, S Zarnack, R Lange, O Donath, T Wohlfahrt… - Machines, 2024 - mdpi.com
Robotic systems are crucial in modern manufacturing. Complex assembly tasks require the
collaboration of multiple robots. Their orchestration is challenging due to tight tolerances …
collaboration of multiple robots. Their orchestration is challenging due to tight tolerances …