Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Obstacle Parameter Modeling for Model Predictive Control of the Unmanned Vehicle

무인자동차의 모델 예측제어를 위한 장애물 파라미터 모델링 기법

  • 여정윤 (건국대학교 전자정보통신공학과) ;
  • 김우현 (서울대학교 전기컴퓨터공학부) ;
  • 임준혁 (건국대학교 전자정보통신공학과) ;
  • 이달호 (가천대학교 전자공학과) ;
  • 지규인 (건국대학교 전자정보통신공학과)
  • Received : 2012.09.24
  • Accepted : 2012.11.03
  • Published : 2012.12.01
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Abstract

The MPC (Model Predictive Control) is one of the techniques that can be used to control an unmanned vehicle. It predicts the future vehicle trajectory using the dynamic characteristic of the vehicle and generate the control value to track the reference path. If some obstacles are detected on the reference paths, the MPC can generate control value to avoid the obstacles imposing the inequality constraints on the MPC cost function. In this paper, we propose an obstacle modeling algorithm for MPC with inequality constraints for obstacle avoidance and a method to set selective constraint on the MPC for stable obstacle avoidance. Simulations with the field test data show successful obstacle avoidance and way point tracking performance.

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References

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