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Eigentaste: A Constant Time Collaborative Filtering Algorithm
- Ken Goldberg, T. Roeder, Dhruv Gupta, Chris Perkins
- Computer ScienceInformation Retrieval
- 1 July 2001
This work compares Eigentaste to alternative algorithms using data from Jester, an online joke recommending system, and uses the Normalized Mean Absolute Error (NMAE) measure to compare performance of different algorithms.
Dex-Net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metrics
- Jeffrey Mahler, Jacky Liang, +5 authors Ken Goldberg
- Computer Science, EngineeringRobotics: Science and Systems
- 27 March 2017
Experiments with over 1,000 trials on an ABB YuMi comparing grasp planning methods on singulated objects suggest that a GQ-CNN trained with only synthetic data from Dex-Net 2.0 can be used to plan grasps in 0.8sec with a success rate of 93% on eight known objects with adversarial geometry.
Motion planning with sequential convex optimization and convex collision checking
- J. Schulman, Yan Duan, +7 authors P. Abbeel
- Mathematics, Computer ScienceInt. J. Robotics Res.
- 1 August 2014
A sequential convex optimization procedure, which penalizes collisions with a hinge loss and increases the penalty coefficients in an outer loop as necessary, and an efficient formulation of the no-collisions constraint that directly considers continuous-time safety are presented.
RLlib: Abstractions for Distributed Reinforcement Learning
This work argues 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, through RLlib: a library that provides scalable software primitives for RL.
A Survey of Research on Cloud Robotics and Automation
- Ben Kehoe, S. Patil, P. Abbeel, Ken Goldberg
- Computer ScienceIEEE Transactions on Automation Science and…
- 12 January 2015
This survey considers robots and automation systems that rely on data or code from a network to support their operation, i.e., where not all sensing, computation, and memory is integrated into a standalone system.
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 during…
Information-Theoretic Planning with Trajectory Optimization for Dense 3D Mapping
- B. Charrow, G. Kahn, +5 authors Vijay R. Kumar
- Computer ScienceRobotics: Science and Systems
- 13 July 2015
An information-theoretic planning approach that enables mobile robots to autonomously construct dense 3D maps in a computationally efficient manner is proposed and reduces the time to explore an environment by 70% compared to a closest frontier exploration strategy and 57%Compared to an information-based strategy that uses global planning.
Dex-Net 1.0: A cloud-based network of 3D objects for robust grasp planning using a Multi-Armed Bandit model with correlated rewards
- Jeffrey Mahler, Florian T. Pokorny, +7 authors Ken Goldberg
- Computer ScienceIEEE International Conference on Robotics and…
- 16 May 2016
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, and reports on system sensitivity to variations in similarity metrics and in uncertainty in pose and friction.
Visual tracking of human visitors under variable-lighting conditions for a responsive audio art installation
- A. Godbehere, Akihiro Matsukawa, Ken Goldberg
- Computer ScienceAmerican Control Conference (ACC)
- 27 June 2012
A single-camera statistical segmentation and tracking algorithm that combines statistical background image estimation, per-pixel Bayesian segmentation, and an approximate solution to the multi-target tracking problem using a bank of Kalman filters and Gale-Shapley matching is introduced.
Deep Imitation Learning for Complex Manipulation Tasks from Virtual Reality Teleoperation
- Tianhao Zhang, Zoe McCarthy, Owen Jow, Dennis Lee, Ken Goldberg, P. Abbeel
- Computer Science, MathematicsIEEE International Conference on Robotics and…
- 12 October 2017
It is described how consumer-grade Virtual Reality headsets and hand tracking hardware can be used to naturally teleoperate robots to perform complex tasks and how imitation learning can learn deep neural network policies that can acquire the demonstrated skills.