US 12,223,739 B2
Obstacle detection system, agricultural work vehicle, obstacle detection program, recording medium on which obstacle detection program is recorded, and obstacle detection method
Shunsuke Edo, Sakai (JP); Kenichi Iwami, Sakai (JP); and Shunsuke Miyashita, Sakai (JP)
Assigned to Kubota Corporation, Osaka (JP)
Appl. No. 17/609,544
Filed by Kubota Corporation, Osaka (JP)
PCT Filed May 20, 2020, PCT No. PCT/JP2020/019932
§ 371(c)(1), (2) Date Nov. 8, 2021,
PCT Pub. No. WO2020/261823, PCT Pub. Date Dec. 30, 2020.
Claims priority of application No. 2019-120480 (JP), filed on Jun. 27, 2019.
Prior Publication US 2022/0230444 A1, Jul. 21, 2022
Int. Cl. G06V 20/58 (2022.01); A01B 69/04 (2006.01); A01B 76/00 (2006.01); A01D 41/127 (2006.01); A01D 75/18 (2006.01); G05D 1/00 (2006.01); G06T 11/00 (2006.01); G06V 10/82 (2022.01)
CPC G06V 20/58 (2022.01) [A01B 69/008 (2013.01); A01B 76/00 (2013.01); A01D 41/127 (2013.01); A01D 75/185 (2013.01); G05D 1/0214 (2013.01); G05D 1/0238 (2013.01); G05D 1/0255 (2013.01); G05D 1/0259 (2013.01); G06T 11/00 (2013.01); G06V 10/82 (2022.01); G06T 2210/22 (2013.01)] 6 Claims
OG exemplary drawing
 
1. An obstacle detection system for an agricultural work vehicle, comprising:
an obstacle sensor configured to detect an obstacle in a field;
an obstacle estimation unit configured to estimate a region in the field based on a detection signal from the obstacle sensor in which region the obstacle is present and output obstacle present region information;
an image capturing unit configured to capture an image of the field and output the captured image;
an image preprocessing unit configured to generate a trimmed image based on the obstacle present region information and shooting-angle-of-view information regarding the image capturing unit which trimmed image is obtained by trimming the captured image so as to include the region in which the obstacle is present; and
an obstacle detection unit configured to receive the trimmed image as an input image and output obstacle detection information that includes a result of the detection of the obstacle,
wherein the obstacle sensor is a scanning sensor that uses ultrasonic beams, optical beams, or electromagnetic wave beams, and outputs the detection signal based on reflection beams that return to the obstacle sensor as a result of transmitted beams reflecting off a reflection body,
wherein the obstacle estimation unit calculates a three-dimensional position of the obstacle from the detection signal with use of the reflection body as the obstacle, and outputs the obstacle present region information including the three-dimensional position,
wherein the obstacle detection unit is configured as a machine-learned neural network, and
wherein the obstacle detection information output based on the input image includes a type of the obstacle.