CAJ | 학술논문

针对无人机没有考虑障碍规避而导致无人机的同时定位与地图构建(simultaneous localization and mapping, SLAM)任务无法完成的问题，提出一种改进的人工势场法。通过建立一个包含无人机到目标点的距离、无人机到障碍物的距离及障碍物方差的势场函数，制定避障策略，从而解决无人机 SLAM的障碍规避问题，并在构建的无人机运动模型基础上，对提出的算法进行仿真验证。仿真结果表明：该算法在完成 SLAM任务的同时，能够有效地避开障碍物的威胁。
침대무인궤몰유고필장애규피이도치무인궤적동시정위여지도구건(simultaneous localization and mapping, SLAM)임무무법완성적문제，제출일충개진적인공세장법。통과건립일개포함무인궤도목표점적거리、무인궤도장애물적거리급장애물방차적세장함수，제정피장책략，종이해결무인궤 SLAM적장애규피문제，병재구건적무인궤운동모형기출상，대제출적산법진행방진험증。방진결과표명：해산법재완성 SLAM임무적동시，능구유효지피개장애물적위협。
When UAV is implementing the simultaneous localization and mapping (SLAM) problem, the environments UAV is flying exist obstacles to be avoided, which threatens the completeness of SLAM mission. To conquer this problem, an improved artificial potential field algorithm is proposed to simultaneously accomplish obstacle avoidance of UAV and SLAM mission by building a potential field function containing the distance from UAV to the goal and from UAV to the obstacles and the covariance of features and constituting avoidance strategy. This algorithm is simulated and tested based on the built UAV plane motion model. The result shows that the proposed algorithm is effective to avoid the obstacles while implementing SLAM for UAV.