7 papers
TT4D: A Pipeline and Dataset for Table Tennis 4D Reconstruction From Monocular Videos
Nima Rahmanian, Daniel Kienzle, Thomas Gossard +3
We present TT4D, a large-scale, high-fidelity table tennis dataset. It provides hours of reconstructed singles and doubles gameplay from monocular broadcast videos, featurin…
DreamControl-v2: Simpler and Scalable Autonomous Humanoid Skills via Trainable Guided Diffusion Priors
Sudarshan Harithas, Sangkyung Kwak, Pushkal Katara +6
Developing robust autonomous loco-manipulation skills for humanoids remains an open problem in robotics. While RL has been applied successfully to legged locomotion, applying it to…
DreamControl: Human-Inspired Whole-Body Humanoid Control for Scene Interaction via Guided Diffusion
Dvij Kalaria, Sudarshan S Harithas, Pushkal Katara +7
We introduce DreamControl, a novel methodology for learning autonomous whole-body humanoid skills. DreamControl leverages the strengths of diffusion models and Reinforcement Learni…
LATTE-MV: Learning to Anticipate Table Tennis Hits from Monocular Videos
Daniel Etaat, Dvij Kalaria, Nima Rahmanian +1
Physical agility is a necessary skill in competitive table tennis, but by no means sufficient. Champions excel in this fast-paced and highly dynamic environment by anticipating the…
α-RACER: Real-Time Algorithm for Game-Theoretic Motion Planning and Control in Autonomous Racing using Near-Potential Function
Dvij Kalaria, Chinmay Maheshwari, Shankar Sastry
Autonomous racing extends beyond the challenge of controlling a racecar at its physical limits. Professional racers employ strategic maneuvers to outwit other competing opponents t…
Agile Mobility with Rapid Online Adaptation via Meta-learning and Uncertainty-aware MPPI
Dvij Kalaria, Haoru Xue, Wenli Xiao +3
Modern non-linear model-based controllers require an accurate physics model and model parameters to be able to control mobile robots at their limits. Also, due to surface slipping…