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Online Tool Selection with Learned Grasp Prediction Models
However, we find that an approximate solution based on sparse tree search yields near optimal performance at a fraction of the time.
Self-Supervised Goal-Conditioned Pick and Place
Robots have the capability to collect large amounts of data autonomously by interacting with objects in the world.
Robotics
Imitation Learning from Visual Data with Multiple Intentions
In this paper we present an LfD approach for learning multiple modes of behavior from visual data.
Training Factor Graphs with Reinforcement Learning for Efficient MAP Inference
Large, relational factor graphs with structure defined by first-order logic or other languages give rise to notoriously difficult inference problems.
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