Yiyang Ling 凌逸飏

I am a first year PhD student in Computer Science at University of Southern California, advised by Prof. Daniel Seita. I received my Bachelor's degree at ACM Honors Class, Shanghai Jiao Tong University.

My research interest lies in robot learning. Previously, I worked as a student intern at University of California San Diego, under the supervision of Prof. Xiaolong Wang. Before this, I gained valuable experience as a research assistant in the SJTU Machine Vision and Intelligence Group, where I was advised by Prof. Cewu Lu.

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Research

IMPACT: Intelligent Motion Planning with Acceptable Contact Trajectories via Vision-Language Models

We introduce IMPACT, a novel motion planning framework that uses Vision-Language Models to infer environment semantics, identifying which parts of the environment can best tolerate contact based on object properties and locations. Results both in simulation and real-world suggest that IMPACT enables robots to efficiently reach targets while making semantically acceptable contact when needed.

GenSim: Generating Robotic Simulation Tasks via Large Language Models

In this work, we propose to automatically generate rich simulation environments and expert demonstrations by exploiting LLMs’ grounding and coding ability. Our approach has two modes: goal-directed generation, wherein LLM proposes a task curriculum to solve a target task, and exploratory generation, wherein LLM bootstraps from previous tasks and iteratively proposes novel complex tasks.

Education

University of Southern California

Ph.D. student in Computer Science

Shanghai Jiao Tong University

B.S. in Computer Science

Design and source code from Leonid Keselman's website