Additional objects will require training a yolov3 model yourself.Īfter an object has been detected you can press t to target an object and pick it up. Available objects as part of yolov3 can be found in models/yolov3.txt. By default it is set up to detect only apples, but this can be changed by passing tracked_object:=other_thing as part of the demo.launch launch command above. If the object is detected a box will appear around it with a label. target objects for pickupįinally, place your object in the field of view.
However, if you move the camera or the arm, you'll need to recalibrate. Then you will be asked to click in the center of the gripper as the robot arm moves around the field of view.Īfter you have calibrated, you can press l on subsequent startups to load the calibration from file. First, you will be prompted to click on the center base of the robot in the image. When you are ready to start, run c for calibrate. H: go to home position (middle to one side)īefore you start objects you need to calibrate a mapping from location in the image to motor angle positions in the Braccio. build projectĬlone this repo into the src folder of a catkin workspace. Then you can use the Arduino IDE to upload the braccio_ros/braccio_ros.ino file to the Arduino running the Braccio arm.
#ARDUINO BRACCIO ROBOTIC ARM INSTALL#
You'll also need to install ROS for Arduino following the instructions here as well as adding the specific library in libraries/BraccioLibRos following the instructions here. upload braccio_ros to assembled Braccioįirst you need an assembled and working Arduino Braccio arm. You will probably also have to add more packages as you go through using something like sudo apt-get install ros-melodic-PACKAGE.
ROS is quite surprisingly awkward to set up, but follow along here and it should get you close to set up. This is a demo project to use an overhead camera and an Arduino Braccio to pick up objects using ROS MoveIt and OpenCV's dnn with YOLOv3 weights. Ros_braccio_opencv_obj_detect_grab Arduino Braccio robotic arm + object detection using OpenCV YOLOv3
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