Pieter Abbeel
Pieter Abbeel is a UC Berkeley professor working at the intersection of robotics and machine learning.
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16 results for “Reinforcement learning”
Pieter Abbeel is a UC Berkeley professor working at the intersection of robotics and machine learning.
A set of methods that fit model behavior from data for tasks such as prediction, classification, perception or control.
G1 is a compact humanoid platform sold in configurations for education, research and development. Prices and configurations can change.
The paper presents a mobile bimanual teleoperation system and imitation-learning experiments for household-style tasks.
The work studies closed-loop grasping learned from a large collection of robot interaction data.
The work applies diffusion models to generate robot action sequences from observations.
The project aggregates robot demonstration data across institutions and studies models trained across different robot embodiments.
Machine learning develops models whose behavior is fitted from data rather than specified only through fixed rules.
Phoenix is Sanctuary AI's general-purpose humanoid platform, paired with the company's AI control system.
Dieter Fox studies robotics, perception and state estimation; the institutional page is the authority for current roles.
Fei-Fei Li is a Stanford professor whose work includes computer vision and human-centered artificial intelligence.
The paper describes vision-language-action models that represent robot actions alongside visual and language inputs.
Computational methods that extract information from images or video, including detection, tracking, segmentation and depth estimation.
Sensor fusion combines measurements from multiple sensors to estimate a system or environment more reliably than a single stream alone.
Autonomous tractor using cameras and machine learning to perform bounded tillage work under remote monitoring.
Camera- and machine-learning-equipped spraying system that identifies crops and weeds for targeted application.