TL;DR
Quantitative experiments showed that the proposed method generally outperformed the baselines in mass and CoM variations, particularly in terms of success rate, while maintaining robust performance across the evaluated conditions.
Two complementary physics priors for robust in-hand rolling manipulation are introduced: a global grasp-quality prior derived from classical grasp analysis and a local contact-geometry prior based on fingertip curvature.
Robotic hands offer advanced manipulation capabilities, but their complexity and cost often limit their real-world applications. In contrast, simple parallel grippers, although affordable, are restricted to basic tasks like pick-and-place. Recently, a vibration-based mechanism was proposed to augment parallel grippers...
Soft grippers enable stable grasping through compliant structures and multipoint contact; however, manipulating the pose of a grasped object while maintaining contact remains challenging, particularly when large pose changes are required. Conventional approaches based on locally estimated drive matrices are limited to...
Dual-arm robots often encounter difficulties when handling easily deformable or structurally complex objects using traditional grasping-based manipulation. In addition, grasping and releasing operations introduce significant time overhead. To address these limitations, this paper proposes a vision-based predictive cont...
An adaptive scheme that estimates the kinematic relationship between a robot's joints and the task features it senses online, using only joint-angle sensing and a wrist-mounted force/torque sensor, with no exteroceptive measurement of the tool tip is developed.
TAC-LOCO is proposed, a tactile-augmented unified reinforcement learning framework that encodes tactile array observations from compliant grippers into a compact latent representation and joins it with proprioception for unified control of the legs, arm, and gripper.
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