Erick Rosete-Beas
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View article: T3VIP: Transformation-based 3D Video Prediction
T3VIP: Transformation-based 3D Video Prediction Open
For autonomous skill acquisition, robots have to learn about the physical rules governing the 3D world dynamics from their own past experience to predict and reason about plausible future outcomes. To this end, we propose a transformation-…
View article: Latent Plans for Task-Agnostic Offline Reinforcement Learning
Latent Plans for Task-Agnostic Offline Reinforcement Learning Open
Everyday tasks of long-horizon and comprising a sequence of multiple implicit subtasks still impose a major challenge in offline robot control. While a number of prior methods aimed to address this setting with variants of imitation and of…
View article: CALVIN: A Benchmark for Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation Tasks
CALVIN: A Benchmark for Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation Tasks Open
General-purpose robots coexisting with humans in their environment must learn to relate human language to their perceptions and actions to be useful in a range of daily tasks. Moreover, they need to acquire a diverse repertoire of general-…
View article: Robot Skill Adaptation via Soft Actor-Critic Gaussian Mixture Models
Robot Skill Adaptation via Soft Actor-Critic Gaussian Mixture Models Open
A core challenge for an autonomous agent acting in the real world is to adapt its repertoire of skills to cope with its noisy perception and dynamics. To scale learning of skills to long-horizon tasks, robots should be able to learn and la…