7 papers
IndoorR2X: Indoor Robot-to-Everything Coordination with LLM-Driven Planning
Fan Yang, Soumya Teotia, Shaunak A. Mehta +8
Although robot-to-robot (R2R) communication improves indoor scene understanding beyond what a single robot can achieve, R2R alone cannot overcome partial observability without subs…
AME-2: Agile and Generalized Legged Locomotion via Attention-Based Neural Map Encoding
Chong Zhang, Victor Klemm, Fan Yang +1
Achieving agile and generalized legged locomotion across terrains requires tight integration of perception and control, especially under occlusions and sparse footholds. Existing m…
DeFM: Learning Foundation Representations from Depth for Robotics
Manthan Patel, Jonas Frey, Mayank Mittal +5
Depth sensors are widely deployed across robotic platforms, and advances in fast, high-fidelity depth simulation have enabled robotic policies trained on depth observations to achi…
SAHA: Supervised Autonomous HArvester for selective forest thinning
Fang Nan, Meher Malladi, Qingqing Li +7
Forestry plays a vital role in our society, creating significant ecological, economic, and recreational value. Efficient forest management involves labor-intensive and complex oper…
Spatially-Enhanced Recurrent Memory for Long-Range Mapless Navigation via End-to-End Reinforcement Learning
Fan Yang, Per Frivik, David Hoeller +3
Recent advancements in robot navigation, particularly with end-to-end learning approaches such as reinforcement learning (RL), have demonstrated strong performance. However, succes…
TartanGround: A Large-Scale Dataset for Ground Robot Perception and Navigation
Manthan Patel, Fan Yang, Yuheng Qiu +4
We present TartanGround, a large-scale, multi-modal dataset to advance the perception and autonomy of ground robots operating in diverse environments. This dataset, collected in va…