Narayanan
Palghat Parameswaran

FCTS: Failure-Guided Curriculum Tree Search Over Generated Terrain for Legged Parkour

Narayanan P. Parameswaran, D. K. Kim, J. Patrikar, …, S. Scherer

When the policy fails on a course, FCTS records where and how it failed, and an LLM uses that to generate new terrain aimed at exactly that weakness. The policy then trains on it, and Monte Carlo Tree Search decides which of several competing curricula deserves more of the compute budget.

GRoQ-LoCO: Generalist and Robot-agnostic Quadruped Locomotion Control using Offline Datasets

Narayanan PP, Sarvesh Prasanth Venkatesan, Srinivas Kantha Reddy, Shishir Kolathaya

One policy, many quadrupeds. A recurrent transformer is trained by offline behavior cloning on 2,000+ expert trajectories per morphology. It fuses stair and flat-ground skills from proprioception alone, with no robot-specific encodings, and runs on a Unitree Go1 and the 20 kg-payload Stoch 5 without fine-tuning.

@article{pp2025groqloco,
  title   = {GRoQ-LoCO: Generalist and Robot-agnostic Quadruped Locomotion Control using Offline Datasets},
  author  = {PP, Narayanan and Venkatesan, Sarvesh Prasanth and Reddy, Srinivas Kantha and Kolathaya, Shishir},
  journal = {arXiv preprint arXiv:2505.10973},
  year    = {2025}
}