In this research, we propose a vision-based human and robot 3D pose estimation algorithm to prevent collision accident. We use two calibrated RGB cameras to estimate 3D position of each joints. In case of robot, we introduce a noble iterative method that estimates joint angles from 2D keypoints. For human 3D pose, we use two-camera-based stereo triangulation which converts 2D keypoint pairs into 3D points. With the estimated 3D joint positions of each object, we can measure Euclidean distances to predict whether they are in danger of collision.

In this study, we develop a Joystick control algorithm for remote berthing and deberthing of an unmanned ship propelled by an waterjet.

We also develop a fully autonomous berthing and deberthing control algorithm of the ship that follows given way point sets and desired for speeds

In this study, an algorithm for autonomous driving of small agricultural tractors on various types of ridges was developed and the performance was verified through experiments. The algorithm was constructed using a deep learning network and depth images to generalize the performance. And the verification process of the algorithm has been completed in various ridge environments.

GPS based autonomous driving rice transplanter sometimes invades the area of planted seedlings when GPS signal is incorrect. To solve this problem, we suggest vision based autonomous vehicle which detects planted area and generates desired driving path