539 citations · 2k across the 41 of their papers we have counts for
3 papers · 1 filter
MBMF: Model-Based Priors for Model-Free Reinforcement Learning
Somil Bansal, Roberto Calandra, Kurtland Chua +2
Reinforcement Learning is divided in two main paradigms: model-free and model-based. Each of these two paradigms has strengths and limitations, and has been successfully applied to…
The Feeling of Success: Does Touch Sensing Help Predict Grasp Outcomes?
Roberto Calandra, Andrew Owens, Manu Upadhyaya +4
A successful grasp requires careful balancing of the contact forces. Deducing whether a particular grasp will be successful from indirect measurements, such as vision, is therefore…
Goal-Driven Dynamics Learning via Bayesian Optimization
Somil Bansal, Roberto Calandra, Ted Xiao +2
Real-world robots are becoming increasingly complex and commonly act in poorly understood environments where it is extremely challenging to model or learn their true dynamics. Ther…