CAJ | 학술논문

针对复杂多变的战场环境中多无人机路径再规划，给出了一种人机合作策略下的改进稀疏A算法。提出在局部路径再规划动态窗口内人工干预给出必经子目标点，再通过SAS算法自动规划出路径的人机交互策略；采用路径再规划约束条件对生成的路径节点进行了合并处理。仿真实验表明，上述改进的SAS算法，有效约束了SAS算法可行解空间，降低了算法的计算量，并且减少了生成路径点的个数，缩短了数据传输时间，获得了多无人机规避突发威胁/危险、避碰的令人主观满意的再规划路径。
침대복잡다변적전장배경중다무인궤로경재규화，급출료일충인궤합작책략하적개진희소A산법。제출재국부로경재규화동태창구내인공간예급출필경자목표점，재통과SAS산법자동규화출로경적인궤교호책략；채용로경재규화약속조건대생성적로경절점진행료합병처리。방진실험표명，상술개진적SAS산법，유효약속료SAS산법가행해공간，강저료산법적계산량，병차감소료생성로경점적개수，축단료수거전수시간，획득료다무인궤규피돌발위협/위험、피팽적령인주관만의적재규화로경。
An improved path replanning sparse A*search algorithm based on the strategy of human-automation col-laboration is proposed for multiple UAVs under complex and dynamic war environment . The proposed strategy is that the sub-goal waypoints can be inserted manually in the dynamic path replanning window through human-auto-mation collaboration with the A*algorithm executing automatically. The replanning waypoints are processed further and merged. Simulation experimental results and their analysis show preliminarily that the above method can obtain an subjectively satisfactory result rapidly, satisfying the requirements of popup-threat avoidance, collision avoidance among multiple paths, reducing search space and computation time, and making the number of replanned waypoints smaller and transmission time shorter.