Ri-Zhao (Roger) Qiu

I am a PhD student at UCSD, working with Prof. Xiaolong Wang. Before this, I received my BS/MS in mathematics and computer science at UIUC, where I worked with Prof. Kris Hauser and Prof. Yuxiong Wang.

During my undergrad, I spent a happy year forming the Illini RoboMaster club in 2018.

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My research interests lie in the intersection of robotics and computer vision. My research aims at enhancing the mobile manipulation capabilities of robots via CV methods.

Egocentric human demonstrations as a data source for humanoid manipulation.

Memory attention to substitute feature distillation.

Long horizon loco-manipulation with LLM planner and learned wholebody skills.

Splatting features enable precise and efficient grasping in dynamic environments.

Synthesizing physics-based particle object motion via feature distillation and MPM.

A sim-to-real framework that enables the robot to grasp different objects in varying surroundings.

Align diffusion models for generation of images and masks of uncommon classes via few-shot conditioning.

Real-time Generalizable Feature Fields enable Mobile Manipulation.

We design a method that enables continual segmentation learning with few annotations via a guided data synthesis process.

We design a disinfection system that can priortize cleaning of high-touch surfaces like human cleaners by co-designing perception and planning algorithms.

We designed and built robots from bolts and metal to perception algorithm. I mainly helped with writing STM32 application software and perception code.

I implemented a codebase for robotics motion planning, which supports common problems like 2D narrow passage, bug traps, and robot arm grasping. It implements a variety of algorithms including RRT, RRT*, bRRT, PRM, FMT. In addition to uniform sampling, it also supports non-uniform sampler using conditional autoencoder.

Borrowed from Jon Barron's source code.