Qt_Yeung's profile picture. Researcher @KTHuniversity in robot learning, manipulation and perception. Prev: @UTAustin and @OrebroUni | Opinions are my own

Quantao Yang

@Qt_Yeung

Researcher @KTHuniversity in robot learning, manipulation and perception. Prev: @UTAustin and @OrebroUni | Opinions are my own

We present OneMap, a zero-shot multi-object navigation method where robots reuse knowledge to search more efficiently! ✅ Open-vocabulary feature maps ✅ Probabilistic semantic updates ✅ SOTA performance in sim & real world Led by @fnnBsch. Read more: finnbsch.github.io/OneMap

onemap.pages.dev

OneMap: Real-time Open-Vocabulary Mapping for Zero-shot Multi-Object Navigation

Efficient object search using open-vocabulary mapping for robotics applications.

How would you find a chair, then a TV, then a bed in an unfamiliar house? Our paper "One Map to Find Them All" enables robots to do this in real-time with semantic memory maps—running on a Jetson & Boston Dynamics Spot! Paper, Code, Video in the reply! ⬇️ #ICRA2025 #Robotics



Mobile manipulation in open-world environments presents significant challenges. Bumble shows its generalization capabilities in long-horizon mobile manipulation tasks by integrating vision-language model (VLM) knowledge. Check out the work from @rutavms !

🤖 Want your robot to grab you a drink from the kitchen downstairs? 🚀 Introducing BUMBLE: a framework to solve building-wide mobile manipulation tasks by harnessing the power of Vision-Language Models (VLMs). 👇 (1/5) 🌐 robin-lab.cs.utexas.edu/BUMBLE



Imitation learning suffers from sample inefficiency and compounding errors. Check out our behavior primitive-based efficient imitation learning PRIME, led by @TianGao_19!

Imitation learning often involves significant human effort to collect a large dataset for robust policy learning. How can we train robust policies in low-data regimes? Our imitation learning framework PRIME scaffolds manipulation tasks with behavior primitives, breaking down…



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