1 citations · 2 across the 11 of their papers we have counts for
11 papers
BayRnTune: Adaptive Bayesian Domain Randomization via Strategic Fine-tuning
Tianle Huang, Nitish Sontakke, K. Niranjan Kumar +4
Domain randomization (DR), which entails training a policy with randomized dynamics, has proven to be a simple yet effective algorithm for reducing the gap between simulation and t…
Words into Action: Learning Diverse Humanoid Robot Behaviors using Language Guided Iterative Motion Refinement
K. Niranjan Kumar, Irfan Essa, Sehoon Ha
Humanoid robots are well suited for human habitats due to their morphological similarity, but developing controllers for them is a challenging task that involves multiple sub-probl…
Learning manipulation of steep granular slopes for fast Mini Rover turning
Deniz Kerimoglu, Daniel Soto, Malone Lincoln Hemsley +4
Future planetary exploration missions will require reaching challenging regions such as craters and steep slopes. Such regions are ubiquitous and present science-rich targets poten…
CrossLoco: Human Motion Driven Control of Legged Robots via Guided Unsupervised Reinforcement Learning
Tianyu Li, Hyunyoung Jung, Matthew Gombolay +2
Human motion driven control (HMDC) is an effective approach for generating natural and compelling robot motions while preserving high-level semantics. However, establishing the cor…
ACE: Adversarial Correspondence Embedding for Cross Morphology Motion Retargeting from Human to Nonhuman Characters
Tianyu Li, Jungdam Won, Alexander Clegg +3
Motion retargeting is a promising approach for generating natural and compelling animations for nonhuman characters. However, it is challenging to translate human movements into se…
Learning and Adapting Agile Locomotion Skills by Transferring Experience
Laura Smith, J. Chase Kew, Tianyu Li +5
Legged robots have enormous potential in their range of capabilities, from navigating unstructured terrains to high-speed running. However, designing robust controllers for highly…