8 citations · 8 across the 4 of their papers we have counts for
4 papers
FELT: Generating Tactile Signals from Vision for Visuo-Tactile Manipulation
Zinan Li, Yiyang Ling, Yuming Gu +8
Tactile sensing can improve performance in contact-rich robot manipulation. However, learning policies that use real tactile feedback typically requires demonstrations collected wi…
Learning Geometry-Aware Nonprehensile Pushing and Pulling with Dexterous Hands
Yunshuang Li, Yiyang Ling, Gaurav S. Sukhatme +1
Nonprehensile manipulation, such as pushing and pulling, enables robots to move, align, or reposition objects that may be difficult to grasp due to their geometry, size, or relatio…
IMPACT: Intelligent Motion Planning with Acceptable Contact Trajectories via Vision-Language Models
Yiyang Ling, Karan Owalekar, Oluwatobiloba Adesanya +2
Motion planning involves determining a sequence of robot configurations to reach a desired pose, subject to movement and safety constraints. Traditional motion planning finds colli…
GenSim: Generating Robotic Simulation Tasks via Large Language Models
Lirui Wang, Yiyang Ling, Zhecheng Yuan +6
Collecting large amounts of real-world interaction data to train general robotic policies is often prohibitively expensive, thus motivating the use of simulation data. However, exi…