Multimodal soft robotic actuation and locomotion

DR Yao, I Kim, S Yin, W Gao - Advanced Materials, 2024 - Wiley Online Library
Diverse and adaptable modes of complex motion observed at different scales in living
creatures are challenging to reproduce in robotic systems. Achieving dexterous movement …

Learning-based legged locomotion: State of the art and future perspectives

S Ha, J Lee, M van de Panne, Z ** with high robustness and low drift
J Zhang, S Singh - Journal of field robotics, 2018 - Wiley Online Library
We present a data processing pipeline to online estimate ego‐motion and build a map of the
traversed environment, leveraging data from a 3D laser scanner, a camera, and an inertial …

Learning robot soccer from egocentric vision with deep reinforcement learning

D Tirumala, M Wulfmeier, B Moran, S Huang… - arxiv preprint arxiv …, 2024 - arxiv.org
We apply multi-agent deep reinforcement learning (RL) to train end-to-end robot soccer
policies with fully onboard computation and sensing via egocentric RGB vision. This setting …

Learning suction graspability considering grasp quality and robot reachability for bin-picking

P Jiang, J Oaki, Y Ishihara, J Ooga, H Han… - Frontiers in …, 2022 - frontiersin.org
Deep learning has been widely used for inferring robust grasps. Although human-labeled
RGB-D datasets were initially used to learn grasp configurations, preparation of this kind of …