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심성대(Sungdae Sim),민지홍(Jihong Min),김병준(Byungjun Kim),김준모(Junmo Kim) 대한전자공학회 2020 대한전자공학회 학술대회 Vol.2020 No.11
Trajectory prediction is one of the important technology for autonomous vehicles and robots. Recently, many learning-based trajectory prediction algorithms are released. Most approaches tend to use recurrent neural networks such as LSTM. Our approach is trajectory prediction using attention mechanisms. Our experiments show the attention mechanism outperforms RNN.
임의 주행 기반 3차원 라이다 좌표와 차량 차표의 외부 파라미터 캘리브레이션 기법
심성대(Sungdae Sim),민지홍(Jihong Min),김준(Jun Kim) 대한기계학회 2016 대한기계학회 춘추학술대회 Vol.2016 No.12
In many autonomous vehicles, 3D LADARs have become a very important sensor. In many case, we put it on someplace of vehicle such as the roof. To integrate sensor informations from time to time, we should know the sensor’s movement. In many applications, we know the movement from the vehicle’s movement via navigation systems such as GPS/IMU or vehicle odometers. When we know the rotations and translations between 3D LADAR and vehicle coordinates, the movement of the sensor can be obtain accurately via a simple transformation. We estimate the extrinsic parameters using iterative closest point algorithm and nonlinear optimization. Experimental results show the proposed algorithm works well.
야지 주행 무인지상차량을 위한 3D 라이다 기반 지면 및 장애물 탐지에 대한 연구
최덕선(Choe, Tok Son),심성대(Sim, Sungdae),민지홍(Min, Jihong) 대한기계학회 2016 대한기계학회 춘추학술대회 Vol.2016 No.12
In this paper, we propose a 3D LIDAR based-obstacle and ground detection algorithm for unmanned ground vehicles driving on rough terrain. We use the Velodyne HDL-32E which is a 32 laser 3D (360°×41.33°) scanning LIDAR. By using the vertical scanning mechanism of this 3D LIDAR, we calculate the gradient of the terrain. For real-time applications, we develop the obstacle and ground detection algorithm by using this gradient. The algorithm is verified by various real experiments.
푸옹 ( Phuong Chu ),조성재 ( Seoungjae Cho ),심성대 ( Sungdae Sim ),곽기호 ( Kiho Kwak ),조경은나 ( Kyungeun Cho ) 한국정보처리학회 2016 한국정보처리학회 학술대회논문집 Vol.23 No.2
In this study we propose a novel approach to segment a terrain in two parts: ground and none-ground. The terrain is gained by a multi-channel 3D laser range sensor. We process each vertical line in each frame data. The vertical line is bounded by the sensor’s position and a point in the largest circle ofthe frame. We consider each pair of two consecutive points in each line to find begin-ground and end-ground points. All points placed between a begin-ground point and an end-ground point are ground ones. The other points are none-ground. After examining all vertical lines in the frame, we obtain the terrain segmentation result.