Humanoid robots are designed to adapt to human workspaces, tackling repetitive or demanding tasks. However, creating general-purpose humanoid robots for real-world tasks and unpredictable environments is challenging. Each of these tasks often requires a dedicated AI model. Training these models from scratch for every new task and environment is a laborious process due to the need for vast task…
]]>Developing effective locomotion policies for quadrupeds poses significant challenges in robotics due to the complex dynamics involved. Training quadrupeds to walk up and down stairs in the real world can damage the equipment and environment. Therefore, simulators play a key role in both safety and time constraints in the learning process. Leveraging deep reinforcement learning (RL) for…
]]>NVIDIA robotics and simulation researchers presented Factory: Fast Contact for Robotic Assembly at the 2022 Robotics: Science and Systems (RSS) conference. This work is a novel breakthrough in the simulation and learning of contact-rich interactions, which are ubiquitous in robotics research. Its aim is to greatly accelerate research and development in robotic assembly, as well as serve as a…
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