3 citations · 4 across the 10 of their papers we have counts for
3 papers · 1 filter
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…
Learning a Single Policy for Diverse Behaviors on a Quadrupedal Robot using Scalable Motion Imitation
Arnaud Klipfel, Nitish Sontakke, Ren Liu +1
Learning various motor skills for quadrupedal robots is a challenging problem that requires careful design of task-specific mathematical models or reward descriptions. In this work…
Residual Physics Learning and System Identification for Sim-to-real Transfer of Policies on Buoyancy Assisted Legged Robots
Nitish Sontakke, Hosik Chae, Sangjoon Lee +3
The light and soft characteristics of Buoyancy Assisted Lightweight Legged Unit (BALLU) robots have a great potential to provide intrinsically safe interactions in environments inv…