Ken Oslund
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View article: Learning to Learn Faster from Human Feedback with Language Model Predictive Control
Learning to Learn Faster from Human Feedback with Language Model Predictive Control Open
Large language models (LLMs) have been shown to exhibit a wide range of capabilities, such as writing robot code from language commands -- enabling non-experts to direct robot behaviors, modify them based on feedback, or compose them to pe…
View article: SARA-RT: Scaling up Robotics Transformers with Self-Adaptive Robust Attention
SARA-RT: Scaling up Robotics Transformers with Self-Adaptive Robust Attention Open
We present Self-Adaptive Robust Attention for Robotics Transformers (SARA-RT): a new paradigm for addressing the emerging challenge of scaling up Robotics Transformers (RT) for on-robot deployment. SARA-RT relies on the new method of fine-…
View article: Robotic Table Tennis: A Case Study into a High Speed Learning System
Robotic Table Tennis: A Case Study into a High Speed Learning System Open
We present a deep-dive into a real-world robotic learning system that, in previous work, was shown to be capable of hundreds of table tennis rallies with a human and has the ability to precisely return the ball to desired targets. This sys…
View article: Robotic Table Tennis: A Case Study into a High Speed Learning System
Robotic Table Tennis: A Case Study into a High Speed Learning System Open
We present a deep-dive into a real-world robotic learning system that, in previous work, was shown to be capable of hundreds of table tennis rallies with a human and has the ability to precisely return the ball to desired targets. This sys…
View article: Barkour: Benchmarking Animal-level Agility with Quadruped Robots
Barkour: Benchmarking Animal-level Agility with Quadruped Robots Open
Animals have evolved various agile locomotion strategies, such as sprinting, leaping, and jumping. There is a growing interest in developing legged robots that move like their biological counterparts and show various agile skills to naviga…