ASIMO: Agent-centric scene representation in multi-object manipulation
Vision-based reinforcement learning (RL) is a generalizable way to control an agent because it is agnostic of specific hardware configurations. As visual observations are highly entangled, attempts for vision-based RL rely on scene representation that ...
Behavior-predefined adaptive control for heterogeneous continuum robots
Continuum robots have great application value and broad prospects in various fields due to their dexterity and compliance. To fully exploit their advantages, it is crucial to develop an effective, accurate and robust control system for them. However, ...
MOB-Net: Limb-modularized uncertainty torque learning of humanoids for sensorless external torque estimation
Momentum observer (MOB) can estimate external joint torque without requiring additional sensors, such as force/torque or joint torque sensors. However, the estimation performance of MOB deteriorates due to the model uncertainty which encompasses the ...
Reduced order modeling of hybrid soft-rigid robots using global, local, and state-dependent strain parameterization
The need for fast and accurate analysis of soft robots calls for reduced order models (ROM). Among these, the relative reduction of strain-based ROMs follows the discretization of the strain to capture the configurations of the robot. Based on the ...