TDMA enables the 2.17 kg MuxArm to drive 10 kg loads at 1% end-effector accuracy even with partial servo failure by multiplexing actuators via hardware switching and a load-reducing trajectory planner.
Design and kinematic modeling of constant curvature continuum robots: A review,
4 Pith papers cite this work. Polarity classification is still indexing.
fields
cs.RO 4verdicts
UNVERDICTED 4representative citing papers
A kinematic boundary-following model with curvature control and Pontryagin-optimal shapes yields a class of continuum grasp quality metrics for planar soft-arm grasping.
A multi-dynamics model integrates electrical, winch, and continuum behaviors in tendon-driven robots to detect contacts and estimate object sizes from motor signals alone.
A rectified flow model trained on 30 actuation-space demonstrations produces control sequences that yield 97.5% grasp success across the workspace, with generalization to object size changes of ±33% and execution speed scaling from 20% to 200%.
citing papers explorer
-
Time-Division Multiplexing Actuation in Tendon-Driven Arms: Lightweight Design and Fault Tolerance
TDMA enables the 2.17 kg MuxArm to drive 10 kg loads at 1% end-effector accuracy even with partial servo failure by multiplexing actuators via hardware switching and a load-reducing trajectory planner.
-
Kinematics of continuum planar grasping
A kinematic boundary-following model with curvature control and Pontryagin-optimal shapes yields a class of continuum grasp quality metrics for planar soft-arm grasping.
-
A Unified Multi-Dynamics Framework for Perception-Oriented Modeling in Tendon-Driven Continuum Robots
A multi-dynamics model integrates electrical, winch, and continuum behaviors in tendon-driven robots to detect contacts and estimate object sizes from motor signals alone.
-
Lightweight Learning from Actuation-Space Demonstrations via Flow Matching for Whole-Body Soft Robotic Grasping
A rectified flow model trained on 30 actuation-space demonstrations produces control sequences that yield 97.5% grasp success across the workspace, with generalization to object size changes of ±33% and execution speed scaling from 20% to 200%.