VISUAL-BASED OBSTACLE DETECTION METHOD AND APPARATUS FOR MOBILE ROBOT

• US 20150314443A1
• Filed: 04/29/2015
• Published: 11/05/2015
• Est. Priority Date: 04/30/2014
• Status: Active Grant

• Current Assignee: Superb Technology Co Ltd
• Original Assignee: Shenzhen Mercury Optoelectronics Research Institute
• Inventors: YU, SHUDA
• Granted Patent: US 9,435,911 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: B25J 9/1666 Avoiding collision or forbidden zones
• CPC Class Codes: B25J 9/1697 Vision controlled systems
• CPC Class Codes: G01V 8/10 Detecting, e.g. by using light barriers by reflection from the object G01S17/00
• CPC Class Codes: G05B 2219/39082 Collision, real time collision avoidance
• CPC Class Codes: G05B 2219/40519 Motion, trajectory planning
• 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 1/0246 using a video camera in combination with image processing means
• CPC Class Codes: G05D 1/0274 using mapping information stored in a memory device navigation using map-matching G01C21/30
• CPC Class Codes: G06T 2207/30244 Camera pose
• CPC Class Codes: G06T 2207/30261 Obstacle
• CPC Class Codes: G06T 7/579 from motion
• CPC Class Codes: G06T 7/73 using feature-based methods
• CPC Class Codes: G06V 20/20 in augmented reality scenes
• CPC Class Codes: Y10S 901/01 Mobile robot

Abstract

A visual-based obstacle detection method is provided. The method includes receiving image information of an environment containing a mobile robot captured by at least one visual sensor to obtain one of a three-dimensional space and a two-dimensional plane, and extracting and matching feature geometric primitives based on the received image information. The method also includes reconstructing coordinates of matched extracted feature geometric primitives and positions and orientations of the visual sensor and optimizing the reconstructed coordinates to obtain a calculation result, wherein the calculation result includes the feature geometric primitives, the positions and orientations of the visual sensor, as well as visible constraint relationships between the feature geometric primitives and the positions and orientations. Further, the method includes detecting obstacles in the environment containing the mobile robot based on the obtained calculation result and plotting a path for automatic motion of the mobile robot based on the detected obstacles.

Claims

1. A visual-based obstacle detection method, comprising:

receiving image information of an environment containing a mobile robot captured by at least one visual sensor to obtain one of a three-dimensional (3D) space and a two-dimensional (2D) plane;

based on the received image information, extracting feature geometric primitives;

based on a certain matching criteria, matching the extracted feature geometric primitives to obtain matched extracted feature geometric primitives;

reconstructing coordinates of the matched extracted feature geometric primitives and positions and orientations of the visual sensor;

optimizing the reconstructed coordinates to obtain a calculation result, wherein the calculation result includes the matched extracted feature geometric primitives, the positions and orientations of the visual sensor, as well as visible constraint relationships between the matched extracted feature geometric primitives and the positions and orientations of the visual sensor;

based on the obtained calculation result, detecting obstacles in the environment containing the mobile robot; and

plotting a path for automatic motion of the mobile robot based on the detected obstacles.

2. The method according to claim 1, wherein detecting obstacles in the environment containing the mobile robot includes:

dividing the 3D space of the environment containing the mobile robot into a plurality of subspaces;

based on at least one of the feature geometric primitives and the visible constraint relationships, marking obstacle subspaces in the plurality of divided subspaces; and

combining the obstacle subspaces into an obstacle space.

3. The method according to claim 2, wherein dividing a 3D space of the environment containing the mobile robot into a plurality of subspaces includes:

dividing the 3D space containing the mobile robot into a plurality of subspaces using one of a regular grid format and an irregular combination structure.

4. The method according to claim 3, wherein dividing the 3D space containing the mobile robot into a plurality of subspaces using a regular grid format further includes:

when a uniform grid structure is used to divide the 3D space, dividing the 3D space into a plurality of subspaces with a preset size; and

when a self-adaptive grid structure is used to divide the 3D space, dividing the 3D space into a plurality of subspaces with a same size, wherein when the size of the subspace is greater than a preset lower limit, and the divided subspace includes the feature geometric primitives, the divided subspace is further divided;

otherwise, the division of the subspace stops.

5. The method according to claim 4, wherein:

the feature geometric primitives include feature geometric points, as well as feature geometric points and feature geometric line segments.

6. The method according to claim 3, wherein dividing the 3D space containing the mobile robot into a plurality of subspaces using an irregular combination structure further includes:

when the feature geometric primitives are the feature geometric points, creating the irregular combination structures using the feature geometric points as vertexes to divide the 3D space into a plurality of irregular polyhedrons; and

when the feature geometric primitives include the feature geometric points and the feature geometric line segments, creating the irregular combination structures by using the feature geometric points as vertexes and using the feature geometric line segments as edges to divide the 3D space into a plurality of irregular polyhedrons.

7. The method according to claim 2, wherein marking obstacle subspaces in the plurality of divided subspaces includes:

marking the subspaces that meet a first preset condition as obstacle subspaces, wherein the first preset condition includes one of the following;

the subspace includes the feature geometric primitive; and

the subspace does not include the feature geometric primitive and the subspace is not intersected with any constraint primitive, wherein the constraint primitive is the primitive constituted by the feature geometric primitive and the position and orientation of the visual sensor which has the visible constraint relationship with the feature geometric primitive.

8. The method according to claim 2, wherein marking obstacle subspaces in the plurality of divided subspaces further includes:

marking the subspaces that meet a second preset condition as obstacle subspaces, wherein the second preset condition is that the subspace is not intersected with any constraint primitive;

and the constraint primitive is the primitive constituted by the feature geometric primitive and the position and orientation of the visual sensor which has the visible constraint relationship with the feature geometric primitive.

9. The method according to claim 2, when a moving space of the mobile robot is the 2D plane, further including:

based on the feature geometric primitives and positions and orientations of the visual sensor, calculating a plurality of 2D plane equations;

selecting a 2D plane equation from the plurality of 2D plane equations to determine the 2D plane;

selecting the feature geometric primitives to be projected from the feature geometric primitives;

projecting the selected feature geometric primitives to be projected and the positions and orientations of the visual sensor to the 2D plane corresponding to the 2D plane equation;

obtaining 2D feature geometric primitives, 2D positions and orientations of the visual sensor, and 2D visible constraint relationships;

dividing the 2D plane into a plurality of plane subspaces; and

based on at least one of the 2D feature geometric primitives and the 2D visible constraint relationships, marking 2D plane obstacle subspaces in the plurality of divided 2D plane subspaces.

10. The method according to claim 2, further including:

when the environment containing the mobile robot changes, determining an updated calculation result and the changed subspaces based on updated image information and the calculation result, wherein the updated calculation result includes updated feature geometric primitives and updated visible constraint relationships; and

based on at least one of the updated feature geometric primitives and the updated visible constraint relationships, re-marking the obstacle subspaces in the changed subspaces.

12. The apparatus according to claim 10, wherein the processing module further includes:

a space division unit configured to divide the 3D space of the environment containing the mobile robot into a plurality of subspaces;

a space marking unit configured to, based on at least one of the feature geometric primitives and the visible constrain relationships, mark obstacle subspaces among the plurality of subspaces divided by the space division unit; and

a combining unit configured to combine the obstacle subspaces marked by the marking unit into an obstacle space.

13. The apparatus according to claim 12, wherein the space division unit further includes:

when a uniform grid structure is used to divide the 3D space, a regular grid division subunit configured to divide the 3D space into a plurality of subspaces with a preset size; and

when a self-adaptive grid structure is used to divide the 3D space, the regular grid division subunit configured to divide the 3D space into a plurality of subspaces with a same size, wherein when the size of the subspace is greater than a preset lower limit, and the divided subspace includes the feature geometric primitives, the divided subspace is further divided;

otherwise, the division of the subspace stops.

14. The apparatus according to claim 12, wherein:

the feature geometric primitives include feature geometric points, as well as feature geometric points and feature geometric line segments.

15. The apparatus according to claim 12, wherein the space division unit further includes:

an irregular combination structure division subunit configured to, when the feature geometric primitives are the feature geometric points, create irregular combination structures by using the feature geometric points as vertexes, and divide the 3D space into a plurality of irregular polyhedrons; and

the irregular combination structure division subunit also configured to, when the feature geometric primitives include the feature geometric points and the feature geometric line segments, create the irregular combination structures by using the feature geometric points as vertexes and using the feature geometric line segments as edges, and divide the 3D space into a plurality of irregular polyhedrons.

16. The apparatus according to claim 12, wherein the space marking unit further includes:

a first space marking subunit configured to mark the subspace that meets a first preset condition as the obstacle subspace, wherein the first preset condition includes one of the following;

the subspace contains the feature geometric primitives; and

the subspace does not contain the feature geometric primitives and the subspace has no intersection with any constraint primitive, wherein the constraint primitive is the primitive constituted by the feature geometric primitive and the position and orientation of the visual sensor which has the visible constraint relationship with the feature geometric primitive.

17. The apparatus according to claim 12, wherein the space marking unit further includes:

a second space marking subunit configured to mark the subspace that meets a second preset condition as the obstacle subspace, wherein the second preset condition is that the subspace has no intersection with any constraint primitive; and

the constraint primitive is the primitive constituted by the feature geometric primitive and the position and orientation of the visual sensor which has the visible constraint relationship with the feature geometric primitive.

18. The apparatus according to claim 12, wherein the processing module further includes:

a plane equation calculation unit configured to, based on the feature geometric primitives and the positions and orientations of the visual sensor, calculate 2D plane equations;

a selection unit configured to select the feature geometric primitives to be projected from the feature geometric primitives; and

a projecting unit configured to project the feature geometric primitives to be projected and the positions and orientations of the visual sensor to the 2D plane corresponding to the 2D plane equation to obtain 2D feature geometric primitives, 2D positions and orientations of the visual sensor, and 2D visible constraint relationships.

19. The apparatus according to claim 12, wherein:

the space division unit is further configured to divide the 2D plane corresponding to the 2D plane equation calculated by the plane equation calculation unit into a plurality of plane subspaces; and

the space marking unit is further configured to, based on at least one of the 2D feature geometric primitives and the 2D visible constraint relationships, mark the plane obstacle subspaces in the plane subspaces divided by the space division unit.

11. A visual-based obstacle detection apparatus, comprising:

a receiving module configured to receive image information of an environment containing a mobile robot captured by at least one visual sensor to obtain one of a three-dimensional (3D) space and a two-dimensional (2D) plane;

a calculation module configured to calculate the image information received by the receiving module using a Visual Simultaneous Localization and Mapping (Visual-SLAM) algorithm to obtain a calculation result, wherein the calculation result includes feature geometric primitives, positions and orientations of the visual sensor, and visible constraint relationships between the feature geometric primitives and the positions and orientations of the visual sensor; and

a processing module configured to, based on the obtained calculation result calculated by the calculation module, detect obstacles in the environment containing the mobile robot.

20. The apparatus according to claim 11, wherein:

the calculation unit is further configured to, when the environment containing the mobile robot changes, determine an updated calculation result and changed subspaces based on updated image information and the calculation result, wherein the updated calculation result includes updated feature geometric primitives and updated visible constraint relationships; and

the processing module is further configured to, based on at least one of the updated feature geometric primitives and the updated visible constraint relationships, re-mark the obstacle subspaces in the changed subspaces.