arXiv Machine Learning
Aug 4

From Digital to Physical Reservoir Computing: Co-Optimizing Soft Robotic Reservoirs via Dynamics Matching

arXiv:2608. 00484v1 Announce Type: cross Abstract: Soft robotic substrates are promising for Physical Reservoir Computing (PRC) because their compliant nonlinear dynamics can provide temporal memory, high-dimensional state transformations, and efficient inference.

By Nicola Visentin, Maximilian St\"olzle, Mariano Ram\'irez Montero, Francesco Braghin, Daniela Rus, Cosimo Della Santina
arXiv AI
Jul 14

Toward Autonomous Soft Robotic Endovascular Navigation via Imitation Learning

arXiv:2510. 09497v2 Announce Type: replace-cross Abstract: In endovascular surgery, endovascular interventionists push a thin tube called a catheter, guided by a thin wire to a treatment site inside the patient's blood vessels to treat various conditions such as blood clots, aneurysms, and malformations.

By Noah Barnes, Ji Woong Kim, Lingyun Di, Hannah Qu, Anuruddha Bhattacharjee, Miroslaw Janowski, Dheeraj Gandhi, Bailey Felix, Shaopeng Jiang, Olivia Young, Mark Fuge, Ryan D. Sochol, Jeremy D. Brown, Axel Krieger
arXiv Machine Learning
Oct 15

Active Exploration in Bayesian Model-based Reinforcement Learning for Robot Manipulation

The paper presents a Bayesian deep learning approach for active exploration in model-based reinforcement learning applied to robot manipulation. By improving model calibration and actively selecting transitions that maximize information gain, the method enhances data efficiency during a preliminary exploration phase. Experiments on a realistic robotic arm simulator demonstrate that the approach achieves comparable performance to existing methods while requiring significantly fewer robot executions.

By Carlos Plou, Ana C. Murillo, Ruben Martinez-Cantin