Humanoid dexterous hands are a core component of embodied intelligence, enabling robots to translate high-level intent into rich and adaptive physical interaction. However, existing designs remain constrained by a persistent trade-off among anthropomorphic kinematic complexity, mechanical robustness, load capacity and...
Ji-Hao Li, Jian-Guo Wang, Hao-Tian Guo et al.· 0 citations
A temperature-coupled viscoelastic force representation is proposed, together with a physics-informed learning model, to reconstruct the force trend and provide explicit compensation during holding, together enabling stable, sustained grasping with soft robotic hands.
Robotic grippers face substantial challenges in grasping and manipulating thin objects. Most existing grippers rely on highly precise approach and grasp motions, which limits robustness and reduces applicability. This paper explores thin-object grasping using books as a representative example. Here, we propose a novel...
