24 citations · 100 across the 25 of their papers we have counts for
7 papers · 1 filter
EmbodiedSWE: Coding Agents for Long Horizon Dexterous Robotics
Haoxiang You, Zeyu Shen, Yilang Liu +16
We study coding agents for long-horizon, dexterous robotics and ask whether their solutions can provide scalable supervision for learning general robot policies. To test this, we d…
HIGenNTO: Scalable Humanoid Interaction Generation via Noise-Space Trajectory Optimization
Lalit Jayanti, Kashu Yamazaki, Yuto Shibata +2
Humanoid robots can acquire complex skills by imitating kinematic humanoid motion references, yet reliable references for contact-rich interactions remain difficult to obtain: moti…
Tactile Genesis: Exploring Tactile Sensors at Scale for Learning Dexterous Tasks
Trinity Chung, Kashu Yamazaki, Dhruv Patel +4
Tactile sensing is critical for contact-rich dexterous manipulation, yet it remains unclear which tactile abstractions a policy needs and when richer tactile fields justify their h…
ExtremControl: Low-Latency Humanoid Teleoperation with Scaled Velocity Feedforward
Ziyan Xiong, Lixing Fang, Junyun Huang +3
Building a low-latency humanoid teleoperation system is essential for collecting diverse reactive and dynamic demonstrations. However, end-to-end latencies in existing approaches c…
Rethinking Progression of Memory State in Robotic Manipulation: An Object-Centric Perspective
Nhat Chung, Taisei Hanyu, Toan Nguyen +9
As embodied agents operate in increasingly complex environments, the ability to perceive, track, and reason about individual object instances over time becomes essential, especiall…
SlotVLA: Towards Modeling of Object-Relation Representations in Robotic Manipulation
Taisei Hanyu, Nhat Chung, Huy Le +10
Inspired by how humans reason over discrete objects and their relationships, we explore whether compact object-centric and object-relation representations can form a foundation for…
RobotArena : Scalable Robot Benchmarking via Real-to-Sim Translation
Yash Jangir, Yidi Zhang, Pang-Chi Lo +7
The pursuit of robot generalists, agents capable of performing diverse tasks across diverse environments, demands rigorous and scalable evaluation. Yet real-world testing of robot…