As personalization technology increasingly orchestrates individualized shopping or
marketing experiences in industries such as logistics, fast-moving consumer goods, and …

This letter presents a novel design of a soft tactile finger with omni-directional adaptation
using multi-channel optical fibers for rigid-soft interactive grasping. Machine learning …

针对工业机器人成本高, 开源性差和维护困难等问题, 设计了一种基于机器视觉的机器人抓取
实验系统. 该系统利用机器视觉, 深度学习和路径规划等技术对目标工件进行识别, 定位 …

Robot arms that assist humans should be able to pick up, move, and release everyday
objects. Today's assistive robot arms use rigid grippers to pinch items between fingers; while …

The engineering design of robotic grippers presents an ample design space for optimization
towards robust grasping. In this letter, we investigate how learning method can be used to …

Neural networks are being increasingly applied to control and decision making for learning-
enabled cyber-physical systems (LE-CPSs). They have shown promising performance …

Bio-inspirations from soft-bodied animals provide a rich design source for soft robots, yet
limited literature explored the potential enhancement from rigid-bodied ones. This paper …

This paper explores the feasibility of learning robot force control and interaction using soft
metamaterial and machine vision. We start by investigating the differential stiffness of a …

Proprioception is the “sixth sense” that detects limb postures with motor neurons. It requires
a natural integration between the musculoskeletal systems and sensory receptors, which is …

Goal-conditioned reinforcement learning is a crucial yet challenging algorithm which
enables agents to achieve multiple user-specified goals when learning a set of skills in a …