University of California

Siemens Aktiengesellschaft

Massachusetts Institute of Technology

The Johns Hopkins University

Catch Tv Acquisition Corp.

Kenneth Y Goldberg

Jeffrey Brian Mahler

Robert J Webster, Iii

Scott F Fullam

Allison Mariko Okamura

Ramu Sharat Chandra

Juan L Aparicio Ojea

Gregory Chirikjian

Noah Cowan

Matthew Matl

Kelly Elizabeth Dobson

Ron Alterovitz

Matthew Lee

Anthony Levandowski

Florian Till Pokorny

Dezhen Song

Dana Spiegel

Yahav Avigal

Derek Tang

Philip D Levinson

John S Gee

Judith Donath

Gregory H Kelly

Jeffrey Ichnowski

Vishal Satish

Eric J Paulos

David Pescovitz

Embodiments are generally directed to generating a training dataset of labelled examples of sensor images and grasp configurations using a set of three-dimensional (3D) models of objects, one or more analytic mechanical representations of either or both of grasp forces and grasp torques, and statistical sampling to model uncertainty in either or both sensing and control. Embodiments can also include using the training dataset to train a function approximator that takes as input a sensor image and returns data that is used to select grasp configurations for a robot grasping or targeting mechanism.

Robotic systems and methods for robustly grasping and targeting objects

Methods and systems are provided for high-speed constrained motion planning. In one embodiment, a method includes computing, with a neural network trained on trajectories generated by a non-convex optimizer, a trajectory from one or more initial states of an autonomous system to one or more final states of the autonomous system, updating, with the non-convex optimizer, the trajectory according to kinematic limits and dynamic limits of the autonomous system to obtain a final trajectory, and automatically controlling the autonomous system from an initial state of the one or more initial states to a final state of the one or more final states according to the final trajectory. In this way, efficient and smooth trajectories can be rapidly computed for effective real-time control while accounting for obstacles and physical constraints of an autonomous system.

Method to optimize robot motion planning using deep learning

A system for analyzing geometric properties for an object includes designing the object in a first computer process and producing information relating to the geometric properties of the object, and receiving the information in a second computer processor which identifies a first portion of the geometric property information as masked or private and second portion identified as public or shared, analysis is performed by the second processor on the public/shared portion of the geometric property information. An output based on the analysis may be provided to an industrial system performing processes on the object. A binary privacy label may be assigned to each triangle in a set of triangles representing the surfaces of the object in a 3D object mesh. The privacy label denotes an associated triangle as being private or shared. The system may be used to produce a set of planned grasps for a robotic gripper.

Method and system for preserving privacy for cloud-based manufacturing analysis services

A collaborative online tele-operation system allows an audience of many participants to simultaneously share control of a single remote actor, such that the actions of the actor are based on the ongoing collective preferences of the audience.

Remote collaborative control and direction

Disclosed is a system for percutaneously steering a surgical needle. Needle steering is accomplished by taking advantage of a deflection force imparted on the bevel tip of the needle by the tissue medium as the needle is pushed through the tissue. By controlling the translation speed and rotation angle of the bevel, a flexible needle may be steered substantially without deflecting or distorting the tissue. The control inputs (translation speed and rotation angle) are computed based on a 'bicycle' non-holonomic kinematic model that is a function of mechanical properties of the tissue medium. The system may be used with image-based feedback, which may provide for feedback-based refinement of the model as the needle propagates through the tissue.

Distal bevel-tip needle control device and algorithm

The method of the invention is executed by a computer under the control of a program stored in computer memory. The method includes the step of accumulating preference data for a set of individuals. The preference data is transformed from multi-dimensional data to lower-dimensional data using a principal component analysis. The lower-dimensional data is then converted into a recommendation map where predicted preference information for a selected individual is easily computed. Recommended content is then routed to the selected individual. The invention has been tested, by way of example, to recommend jokes to users based on their ratings of sample jokes.

Apparatus and method for recommending to an individual selective information contained within a computer network

A system for bookmarking viewer selected TV broadcast events and displaying a set of associated internet locations or website hotlinks, comprising the selection of a set of broadcast events using a remote control, and storing a set of event-identifier data associated with the set of selected broadcast events in an activity table, and then generating a set of associated internet locations or website hotlinks by comparing the set of event identifiers with a database of TV schedules, events and company information. The generated set of associated internet locations or website hotlinks can then be used by viewer for access to and display of the selected internet locations associated with the set of selected broadcast events.

Television event marking system

Growing community of inventors

San Francisco, CA, United States of America

Kenneth Y Goldberg