Safety Validation of Black-Box Autonomous Systems
Robotics Posts | SAIL Blog
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1M ago
Validation of safety-critical autonomous systems is necessary before deployment and is made possible by black-box validation strategies. In this blog post, we provide a model for black-box safety validation and survey the literature to uncover the most effective validation techniques ..read more
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Learning to Influence Multi-Agent Interaction
The Stanford AI Lab Blog » Robotics
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1M ago
We introduce a framework for multi-agent interaction that represents the low-level policies of non-stationary agents with high-level latent strategies ..read more
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GTI: Learning to Generalize Across Long-Horizon Tasks from Human Demonstrations
The Stanford AI Lab Blog » Robotics
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1M ago
We developed Generalization Through Imitation (GTI) - an algorithm for learning visuomotor control from human demonstrations and generalizing to new long-horizon tasks by leveraging latent compositional structures ..read more
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What Matters in Learning from Offline Human Demonstrations for Robot Manipulation
The Stanford AI Lab Blog » Robotics
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1M ago
We conducted an extensive study of six offline learning algorithms for robot manipulation on five simulated and three real-world multi-stage manipulation tasks of varying complexity, and with datasets of varying quality. Our study analyzes the most critical challenges when learning from offline h ..read more
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IGibson: A Simulation Environment to Train AI Agents in Large Realistic Scenes
Robotics Posts | SAIL Blog
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1M ago
Introducing iGibson, an open source, fully academically developed simulation environment for interactive tasks in large realistic scenes ..read more
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Reward Isn't Free: Supervising Robot Learning with Language and Video from the Web
The Stanford AI Lab Blog » Robotics
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1M ago
Where do the rewards for robotic reinforcement learning come from? In this blog post we study how using crowdsourced language annotations and videos of humans, we can learn reward functions in a scalable way and enable them to generalize more broadly ..read more
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Learning to Imitate
The Stanford AI Lab Blog » Robotics
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1M ago
SOTA methods for Imitation Learning are heavily data-inefficient or rely on unstable Adversarial training. We present a novel framework that introduces simple, stable, and data-efficient learning from few experts that scales well to complex environments ..read more
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Stanford AI Lab Papers and Talks at CVPR 2023
Robotics Posts | SAIL Blog
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1M ago
All the great work from the Stanford AI Lab accepted at CVPR 2023, all in one place ..read more
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Self-Improving Robots: Embracing Autonomy in Robot Learning
The Stanford AI Lab Blog » Robotics
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1M ago
Learning methods for robotics have a data problem. Autonomous robotic systems can deliver orders of magnitude more real-world embodied data than we have ..read more
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