Method, system and apparatus for path control in unmanned vehicles

Patent metadata

Field	Value
Publication number	US-9963155-B2
Application number	US-201615164280-A
Country	US
Kind code	B2
Filing date	May 25, 2016
Priority date	May 29, 2015
Publication date	May 8, 2018
Grant date	May 8, 2018

Abstract

A system for path control for a mobile unmanned vehicle in an environment is provided. The system includes: a sensor connected to the mobile unmanned vehicle; the mobile unmanned vehicle configured to initiate a first fail-safe routine responsive to detection of an object in a first sensor region adjacent to the sensor; and a processor connected to the mobile unmanned vehicle. The processor is configured to: generate a current path based on a map of the environment; based on the current path, issue velocity commands to cause the mobile unmanned vehicle to execute the current path; responsive to detection of an obstacle in a second sensor region, initiate a second fail-safe routine in the mobile unmanned vehicle to avoid entry of the obstacle into the first sensor region and initiation of the first fail-safe routine.

First claim

We claim:

1. A system for path control for a mobile unmanned vehicle in an environment, comprising:
a sensor connected to the mobile unmanned vehicle; the mobile unmanned vehicle configured to initiate a first fail-safe routine responsive to detection of an object in a first sensor region adjacent to the sensor; and
a processor connected to the mobile unmanned vehicle, the processor configured to:
generate a current path based on a map of the environment;
based on the current path, issue velocity commands to cause the mobile unmanned vehicle to execute the current path;
responsive to detection of an obstacle in a second sensor region, initiate a second fail-safe routine in the mobile unmanned vehicle to avoid entry of the obstacle into the first sensor region and initiation of the first fail-safe routine.

2. The system of claim 1 , wherein the first fail-safe routine is an emergency stop.

3. The system of claim 2 , the mobile unmanned vehicle configured to initiate the emergency stop by overriding the velocity commands with a halt command.

4. The system of claim 1 , the first sensor region defined by a first range from the mobile unmanned vehicle.

5. The system of claim 4 , the first sensor region comprising one of a point, an area and a volume.

6. The system of claim 4 , the second sensor region defined by a second range from the mobile unmanned vehicle, the second range being greater than the first range.

7. The system of claim 6 , the second sensor region comprising one of a point, an area and a volume.

8. The system of claim 6 , the processor further configured to:
receive sensor data from the sensor; and
detect the obstacle in the second sensor region by determining, based on the sensor data, whether a distance between the mobile unmanned vehicle and the obstacle is smaller than the second range.

9. The system of claim 6 , further comprising:
a second sensor connected to the mobile unmanned vehicle; the processor further configured to:
receive sensor data from the second sensor; and
detect the obstacle in the second sensor region by determining, based on the sensor data, whether a distance between the mobile unmanned vehicle and the obstacle is smaller than the second range.

10. The system of claim 6 , the processor further configured to:
responsive to issuing the velocity commands, setting the first range and the second range based on a measured speed of the mobile unmanned vehicle.

11. The system of claim 10 , the processor further configured to set the first range by:
determining a stopping distance of the mobile unmanned vehicle based on the measured speed; and
setting the first range to be equal to or greater than the stopping distance.

12. The system of claim 11 , the processor further configured to set the first range by instructing the sensor to operate in one of a plurality of discrete modes each having predetermined first ranges, the one of the plurality of discrete modes having a first range equal to or greater than the stopping distance.

13. The system of claim 10 , the processor further configured to set the second range by generating a predicted future position of the mobile unmanned vehicle based on the measured speed.

14. The system of claim 10 , the processor further configured to set the second range as a predetermined multiple of the first range.

15. The system of claim 10 , the processor configured to initiate the second fail-safe routine by:
initiating generation of a new path;
during generation of the new path, issuing velocity commands having adjusted speeds to cause the mobile unmanned vehicle to execute the current path at the adjusted speeds.

16. The system of claim 15 , the processor configured to generate the adjusted speeds by:
selecting a speed;
setting a simulated second sensor region range based on the speed;
determining whether the obstacle falls within the simulated second sensor range; and
reducing the speed and repeating the simulation of the second sensor region range until the obstacle does not fall within the simulated second sensor range.

17. The system of claim 16 , the processor further configured, when the generation of the new path is complete, to:
replace the new path with the current path;
repeat the issuing of velocity commands and the initiation of the second fail-safe routine responsive to detection of a further obstacle in the second sensor region.

18. The system of claim 1 , further comprising:
a housing of the mobile unmanned vehicle containing the processor;
a locomotive device connected to the housing and configured to respond to the velocity commands.

19. The system of claim 1 , the processor further configured to generate the map based on sensor data.

20. The system of claim 19 , the processor further configured to detect the obstacle in the second sensor region based on the map.

Assignees

• Clearpath Robotics Inc

Inventors

• Gariepy Ryan Christopher
• Bencz Alex
• Ma Yan
• Irvine Michael
• Kaynama Shahab
• Servos James
• Chen Peiyi

Classifications

• G05D1/0088

  characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours (using knowledge based models G06N5/00) · CPC title

• B61L3/008

  Operations & Transport · mapped topic

• G05D2201/0212

  Physics · mapped topic

• B61L15/0072

  On-board train data handling · CPC title

• G05D1/0066

  for limitation of acceleration or stress · CPC title