5 papers
ViBe: Visual Behavior Adaptation for Perceptive Humanoid Whole-Body Control
Lokesh Krishna, Sarvesh Venkatesan, An Zhang +1
Motion tracking provides a scalable recipe for humanoid whole-body control. By design, the resulting trackers lack exteroceptive feedback hence reacting to the environment remains…
DiffCoTune: Differentiable Co-Tuning for Cross-domain Robot Control
Lokesh Krishna, Sheng Cheng, Junheng Li +2
The deployment of robot controllers is hindered by modeling discrepancies due to necessary simplifications for computational tractability or inaccuracies in data-generating simulat…
Preferenced Oracle Guided Multi-mode Policies for Dynamic Bipedal Loco-Manipulation
Prashanth Ravichandar, Lokesh Krishna, Nikhil Sobanbabu +1
Dynamic loco-manipulation calls for effective whole-body control and contact-rich interactions with the object and the environment. Existing learning-based control synthesis relies…
OGMP: Oracle Guided Multi-mode Policies for Agile and Versatile Robot Control
Lokesh Krishna, Nikhil Sobanbabu, Quan Nguyen
The efficacy of reinforcement learning for robot control relies on the tailored integration of task-specific priors and heuristics for effective exploration, which challenges their…
Learning Multimodal Bipedal Locomotion and Implicit Transitions: A Versatile Policy Approach
Lokesh Krishna, Quan Nguyen
In this paper, we propose a novel framework for synthesizing a single multimodal control policy capable of generating diverse behaviors (or modes) and emergent inherent transition…