most citedLearning Friction Model for Tethered Capsule Robot

1 citations · 3 across the 6 of their papers we have counts for

collaborators

6 papers

cs.RO2021

Learning Friction Model for Magnet-actuated Tethered Capsule Robot

Yi Wang, Yuyang Tu, Yuchen He +4

The potential diagnostic applications of magnet-actuated capsules have been greatly increased in recent years. For most of these potential applications, accurate position control o…

cs.RO20211 cited

Learning Based Adaptive Force Control of Robotic Manipulation Based on Real-Time Object Stiffness Detection

Zhaoxing Deng, Xutian Deng, Miao Li

Force control is essential for medical robots when touching and contacting the patient's body. To increase the stability and efficiency in force control, an Adaption Module could b…

cs.RO20211 cited

Learning Friction Model for Tethered Capsule Robot

Yi Wang, Yuchen He, Xutian Deng +3

With the potential applications of capsule robots in medical endoscopy, accurate dynamic control of the capsule robot is becoming more and more important. In the scale of a capsule…

cs.RO2021

Learning Dynamical System for Grasping Motion

Xiao Gao, Miao Li, Xiaohui Xiao

Dynamical System has been widely used for encoding trajectories from human demonstration, which has the inherent adaptability to dynamically changing environments and robustness to…

cs.RO20211 cited

Data Generation for Learning to Grasp in a Bin-picking Scenario

Yiting Chen, Miao Li

The rise of deep learning has greatly transformed the pipeline of robotic grasping from model-based approach to data-driven stream. Along this line, a large scale of grasping data…

cs.RO2021

Unknown Object Segmentation through Domain Adaptation

Yiting Chen, Chenguang Yang, Miao Li

The ability to segment unknown objects in cluttered scenes has a profound impact on robot grasping. The rise of deep learning has greatly transformed the pipeline of robotic graspi…