6 citations · 7 across the 4 of their papers we have counts for
5 papers
FlexWorm: Primitive-augmented Hybrid Contact-motion Planning for Suction-based Multi-segment Deformable Robots
Zili Tang, Tiecheng Guo, Qinyue Zhang +1
Multi-segment suction-based soft robots are promising for inspection and maintenance in confined or fragile environments, but existing approaches still depend heavily on manually d…
PushingBots: Collaborative Pushing via Neural Accelerated Combinatorial Hybrid Optimization
Zili Tang, Ying Zhang, Meng Guo
Many robots are not equipped with a manipulator and many objects are not suitable for prehensile manipulation (such as large boxes and cylinders). In these cases, pushing is a simp…
Robust Visual Servoing under Human Supervision for Assembly Tasks
Victor Nan Fernandez-Ayala, Jorge Silva, Meng Guo +1
We propose a framework enabling mobile manipulators to reliably complete pick-and-place tasks for assembling structures from construction blocks. The picking uses an eye-in-hand vi…
RoboCopilot: Human-in-the-loop Interactive Imitation Learning for Robot Manipulation
Philipp Wu, Yide Shentu, Qiayuan Liao +5
Learning from human demonstration is an effective approach for learning complex manipulation skills. However, existing approaches heavily focus on learning from passive human demon…
Collaborative Planar Pushing of Polytopic Objects with Multiple Robots in Complex Scenes
Zili Tang, Yuming Feng, Meng Guo
Pushing is a simple yet effective skill for robots to interact with and further change the environment. Related work has been mostly focused on utilizing it as a non-prehensile man…