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Eigentaste: A Constant Time Collaborative Filtering Algorithm
TLDR
Eigentaste is a collaborative filtering algorithm that uses universal queries to elicit real-valued user ratings on a common set of items and applies principal component analysis (PCA) to the resulting dense subset of the ratings matrix. Expand
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Dex-Net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metrics
TLDR
To reduce data collection time for deep learning of robust robotic grasp plans, we explore training from a synthetic dataset of 6.7 million point clouds, grasps, and analytic grasp metrics generated from thousands of 3D models. Expand
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Motion planning with sequential convex optimization and convex collision checking
TLDR
We present a new optimization-based approach for robotic motion planning among obstacles. Expand
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A Survey of Research on Cloud Robotics and Automation
TLDR
The Cloud infrastructure and its extensive set of Internet-accessible resources has potential to provide significant benefits to robots and automation systems that rely on data or code from a network to support their operation, i.e., where all sensing, computation, and memory is integrated into a standalone system. Expand
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LQG-MP: Optimized path planning for robots with motion uncertainty and imperfect state information
In this paper we present LQG-MP (linear-quadratic Gaussian motion planning), a new approach to robot motion planning that takes into account the sensors and the controller that will be used duringExpand
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RLlib: Abstractions for Distributed Reinforcement Learning
TLDR
We argue for distributing RL components in a composable way by adapting algorithms for top-down hierarchical control, thereby encapsulating parallelism and resource requirements within short-running compute tasks. Expand
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Visual tracking of human visitors under variable-lighting conditions for a responsive audio art installation
TLDR
We introduce a single-camera statistical segmentation and tracking algorithm that improves recall and F2-score over existing methods in OpenCV 2.1 in a variety of situations. Expand
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Dex-Net 1.0: A cloud-based network of 3D objects for robust grasp planning using a Multi-Armed Bandit model with correlated rewards
TLDR
This paper presents the Dexterity Network (Dex-Net) 1.0, a dataset of 3D object models and a sampling-based planning algorithm to explore how Cloud Robotics can be used for robust grasp planning. Expand
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Information-Theoretic Planning with Trajectory Optimization for Dense 3D Mapping
TLDR
We propose an information-theoretic planning approach that enables mobile robots to autonomously construct dense 3D maps in a computationally efficient manner. Expand
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Deep Imitation Learning for Complex Manipulation Tasks from Virtual Reality Teleoperation
TLDR
In this paper we describe how consumer-grade Virtual Reality headsets and hand tracking hardware can be used to naturally teleoperate robots to perform complex tasks. Expand
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