Object detection system

• US 20070019181A1
• Filed: 04/19/2004
• Published: 01/25/2007
• Est. Priority Date: 04/17/2003
• Status: Abandoned Application

• Current Assignee: Jay Gainsboro, Kenneth Sinclair, Lee Weinstein
• Original Assignee: Jay Gainsboro, Kenneth Sinclair, Lee Weinstein
• Inventors: Gainsboro, Jay, Weinstein, Lee, Sinclair, Kenneth
• Application Number:
  US10/553,621
• Publication Number:
  US 20070019181A1
• Time in Patent Office: Days
• US Class Current: 356/4.10
• CPC Class Codes: G01C 3/08 Use of electric radiation detectors
• CPC Class Codes: G01S 17/48 Active triangulation systems, i.e. using the transmission and reflection of electromagnetic waves other than radio waves
• CPC Class Codes: G01S 17/89 for mapping or imaging
• CPC Class Codes: G01S 17/931 of land vehicles
• CPC Class Codes: G05D 1/0214 in accordance with safety or protection criteria, e.g. avoiding hazardous areas monitoring the location of vehicles within a certain area, e.g. forbidden or allowed areas, in traffic control systems for road vehicles G08G1/13
• CPC Class Codes: G05D 1/0248 in combination with a laser lasers per se H01S
• CPC Class Codes: G05D 1/0274 using mapping information stored in a memory device navigation using map-matching G01C21/30
• CPC Class Codes: G06V 10/145 Illumination specially adapted for pattern recognition, e.g. using gratings
• CPC Class Codes: G06V 20/58 Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
• CPC Class Codes: G08G 1/161 Decentralised systems, e.g. inter-vehicle communication

Abstract

An object detection system utilizing one or more thin, planar structured light patterns projected into a volume of interest, along with digital processing hardware and one or more electronic imagers looking into the volume of interest. Triangulation is used to determine the intersection of the structured light pattern with objects in the volume of interest. Applications include navigation and obstacle avoidance systems for autonomous vehicles (including agricultural vehicles and domestic robots), security systems, and pet training systems.

Claims

1. An object detection system, comprising:

A structured light source capable of projecting a first pattern of structured light from a small aperture, said first pattern of structured light falling within a thin planar volume of space;

A first electronic imager not co-planar with said first pattern of structured light, said imager arranged in a pre-determined spatial relationship to said aperture, and said imager imaging a region of space in which objects could intersect said first projected pattern of structured light;

Means for storing at least one electronic images; and

Means calculating object positions from the positions in which structured light appears in a plurality of images.

2. The object detection system of claim 1, further comprising means for performing dead reckoning, said dead reckoning means arranged in a pre-determined spatial relationship to said aperture.

3. The object detection system of claim 1, further comprising means for storing object map information about positions of detected objects.

4. The object detection system of claim 1, further comprising means for indicating an alarm condition if objects enter a volume of space where objects should not be allowed.

5. The object detection system of claim 1, further comprising means for taking automated corrective action if objects enter a volume of space where objects should not be allowed.

6. An object detection method, comprising:

Projecting through a first small aperture a first structured light pattern within a first thin planar volume of space in which it is desired to measure the position of objects;

Capturing and storing at least one image from a first electronic imager positioned in a predetermined spatial relationship to said first small aperture;

Digitally processing at least one captured image to determine positions of objects intersecting said first structured light pattern.

7. The method of claim 6, wherein said step of capturing at least one electronic image comprises capturing a plurality of images and further comprising the step of moving said electronic imager relative to said objects between capturing at least two of said plurality of images, while maintaining the spatial relationship between said first electronic imager and said first optical aperture.

8. The method of claim 6, wherein said step of capturing at least one electronic image comprises capturing a plurality of images, through a plurality of spatially substantially non-coincident electronic imagers.

9. The method of claim 6, wherein said step of capturing at least one electronic image comprises capturing a plurality of images through said first electronic imager, and wherein said step of digitally processing at least one captured image comprises processing a plurality of captured images in such a way as to improve signal to noise ratio, and spatial resolution.

10. The method of claim 6, wherein said step of capturing at least one electronic image comprises capturing a plurality of images through said first electronic imager, and varying the plane of said structured light pattern between capturing at least two of said plurality of images such that images are captured of objects intersecting a plurality of thin planer structured light patterns, and said step of digitally processing at least one captured image comprises processing a said plurality of images captured of intersections of objects with said plurality of varied-plane structured light patterns, to derive a three-dimensional representation of the intersection of objects with said plurality of planar structured light patterns.

11. The method of claim 7, further comprising combining dead-reckoning data with object position data from a plurality of electronic images captured from a plurality of positions of said electronic imager, to produce a three-dimensional representation of objects within a volume of interest.

12. The method of claim 10, further comprising combining dead-reckoning data with redundantly derived object position data from a plurality of electronic images captured from a plurality of positions of said electronic imager imaging intersections of objects with a plurality of planar structured light patterns, to produce a three-dimensional representation of objects within a volume of interest which has less position-dependent position error than a three-dimensional representation derived from a single position of said electronic imager.