Dexterous in-hand manipulation in robotics, particularly with multi-fingered robotic hands, poses significant challenges due to the intricate avoidance of collisions among fingers and the object being manipulated. Collision-free paths for all fingers must be generated in real-time, as the rapid changes in hand and finger positions necessitate instantaneous recalculations to … [Read more...] about Enhancing Dexterity in Confined Spaces: Real-Time Motion Planning for Multifingered In-Hand Manipulation
Training
Visuo-Tactile Recognition of Partial Point Clouds Using PointNet and Curriculum Learning
This article is about recognizing handheld objects from incomplete tactile observations with a classifier trained on only visual representations. Our method is based on the deep learning (DL) architecture PointNet and a curriculum learning (CL) technique for fostering the learning of descriptors robust to partial representations of objects. The learning procedure gradually … [Read more...] about Visuo-Tactile Recognition of Partial Point Clouds Using PointNet and Curriculum Learning
