Action Chunking with Transformers (ACT)
Action Chunking with Transformers (ACT) is an imitation learning algorithm for fine-grained robotic manipulation that predicts a short sequence (a "chunk") of future actions at once instead of a single next…
Robotics
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Showing 1-12 of 12 articles
Behavioral Cloning
Behavioral cloning is the approach to imitation learning that reduces control to a supervised learning problem.
Chelsea Finn
Chelsea Finn (born October 8, 1992) is an American computer scientist, an assistant professor of computer science and electrical engineering at Stanford University, and a co-founder of the robotics company…
Deepak Pathak
Deepak Pathak is an Indian American roboticist and machine learning researcher who is the co-founder and chief executive officer of Skild AI, a startup building a general purpose foundation model for robotics.
DoorDash
DoorDash, Inc. is an American on-demand local commerce and food-delivery company that uses applied machine learning to run a real-time logistics marketplace connecting consumers, merchants, and couriers.
Imitation Learning
Imitation learning is a family of methods for learning sequential behavior from demonstrations.
Kalman Filter
The Kalman filter is a recursive algorithm that estimates the hidden state of a dynamic system from a sequence of noisy measurements.
Large Behavior Model
A Large Behavior Model (LBM) is a single neural network for robotics that is pretrained on large, diverse datasets of robot demonstrations and outputs robot actions
Particle Filter
A particle filter is a simulation-based method for estimating the changing, unobserved state of a system from a sequence of noisy observations.
Robot learning
Robot learning studies how robots acquire or improve behavior from data and experience.
Sensor fusion
Sensor fusion is the process of combining data from multiple sensors, often of different types, to produce information that is more accurate, complete, or reliable than any single sensor could provide on its…
Universal Manipulation Interface
Universal Manipulation Interface (UMI) is an open-source system for collecting robot manipulation training data with a handheld, camera-equipped gripper instead of an actual robot.