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Robot Localization using Object Detection

Estimation of change in position using object tracking and a depth map.

Description of Method

A Microsoft Kinect 360 is used. An RGB image is passed through YOLOv3 to detect 'objects of interest'. The locations of these objects are looked up in a depth map (obtained from freenect_stack with ROS Kinetic) to obtain the spherical coordinates of the object. If these objects are also found in consicutive images, the relative displacement in their vectors is used to calculate the displacement of the robot.

Getting Started

Prerequisites:

  • opencv (cv2)
  • darknet
  • ROS Kinetic (For getting data from Kinect)
  • freenect_stack
  • image_view
  • YOLOv3.weights

Cloning

Clone the repsitory on your local machine by running the following command

git clone hhtp://github.com/rmvanarse/slam_cogneuro

Installations

OpenCV 2.0 pip3 install opencv-python https://pypi.org/project/opencv-python

(Requires: pip3)

freenect_stack http://wiki.ros.org/freenect_stack

YOLOv3.weights

Download the weights file from https://pjreddie.com/media/files/yolov3.weights

Alternatively, run the command wget https://pjreddie.com/media/files/yolov3.weights

Save the yolov3.weights file in the YOLOv3 folder

Running

Viewing RGB and Depth images

Run the following commands in separate terminals after ROS setup is sourced.

roslaunch freenect_launch freenect.launch

rosrun image_view image_view image:=/camera/rgb/image_color

rosrun image_view disparity_view image:=/camera/depth/disparity

Getting the displacement

Run the following commands after enterong the YOLOv3 folder by cd YOLOv3

- python3 yolo_opencv.py --image1 <image1>.jpg --image2 <image2>.jpg --depthImage1 <depth1>.pgm --depthImage2 <depth2>.pgm --config yolov3.cfg --weights yolov3.weights --classes yolov3.txt

- python3 yolo_opencv.py --image1 ../RGBD_img/Mul_exp1-1-rgb.png --image2 ../RGBD_img/Mul_exp1-2-rgb.png --depthImage1 ../RGBD_img/Mul_exp1-1-depth.png --depthImage2 ../RGBD_img/Mul_exp1-2-depth.png --config yolov3.cfg --weights yolov3.weights --classes yolov3.txt

Example:

python3 yolo_opencv.py --image1 r-1.ppm --image2 r-2.ppm --depthImage1 d-1.pgm --depthImage2 d-2.pgm --config yolov3.cfg --weights yolov3.weights --classes yolov3.txt

Built with

  • Python3
  • ROS Kinetic
  • YOLOv3
  • Pytorch
  • CV2
  • Freenect

Limitations

  • Revolution around a single object cannot be detected.
  • Algortihm needs to be modified to differentiate between Yaw and X-displacement of the robot.
  • Requires multiple objects in the frame for a good efficiency
  • Will have to be combined with other odometry methods.

Contributers