US 10,503,976 B2 · Methods and apparatus for autonomous robotic control

Abstract

Sensory processing of visual, auditory, and other sensor information (e.g., visual imagery, LIDAR, RADAR) is conventionally based on “stovepiped,” or isolated processing, with little interactions between modules. Biological systems, on the other hand, fuse multi-sensory information to identify nearby objects of interest more quickly, more efficiently, and with higher signal-to-noise ratios. Similarly, examples of the OpenSense technology disclosed herein use neurally inspired processing to identify and locate objects in a robot's environment. This enables the robot to navigate its environment more quickly and with lower computational and power requirements.

Claims23

Dependent claims

A method comprising:

acquiring a plurality of images of at least a portion of an environment with an image sensor;
constructing a spatial shroud fitting a form of an object in a first image of the plurality of images from the first image;
identifying the object in the first image based at least in part on the spatial shroud;
translating and/or transforming the spatial shroud based at least in part on a change in a position and/or an orientation of the image sensor;
determining if the spatial shroud fits the form of the object in a second image in the plurality of images;
and
in response to determining that the spatial shroud fits the form of the object, identifying a position of the object in the environment based at least in part on the spatial shroud.

4 more elements

Dependencies are inferred from the claim text.

Facts

Application

15/463,299Filed 20 Mar 2017 · continuation

Priority

19 Mar 2014

Published

US 2017/0193298 A16 Jul 2017

Granted

10 Dec 2019

Term ends

Not estimatedThe source records don’t support an estimate.

Classification20 codes

G06N 3/049
Architecture, e.g. interconnection topology: temporal neural networks, e.g. delay elements, oscillating neurons or pulsed inputs
B25J 9/1697
Characterised by use of sensors other than normal servo-feedback from position, speed or acceleration sensors, perception control, multi-sensor…:…
G06N 3/0409
Architecture, e.g. interconnection topology: adaptive resonance theory [ART] networks
G06N 3/088
Learning methods: non-supervised learning, e.g. competitive learning

Family

Application61/955,756Us provisional application · filed 19 Mar 2014

Application14/662,657Parent of this continuation · filed 19 Mar 2015

US 2017/0193298 A1Pre-grant publication · published 6 Jul 2017

US 9,626,566 B2Parent of this continuation

US 2015/0269439 A1Published application

US 10,503,976 B2This patent

From the US filing history. Foreign family members aren’t listed.

Methods and apparatus for autonomous robotic control

Life of this patent

Methods and apparatus for autonomous robotic control

Life of this patent

Abstract

Claims23