机译:超声波车辆的实时再入轨迹规划:一种掺入模糊多目标转录和深神经网络的两步策略
Cranfield Univ Sch Aerosp Transport & Mfg Cranfield MK43 0AL Beds England;
Cranfield Univ Sch Aerosp Transport & Mfg Cranfield MK43 0AL Beds England;
Cranfield Univ Sch Aerosp Transport & Mfg Cranfield MK43 0AL Beds England;
Beijing Inst Technol Sch Automat Beijing 100811 Peoples R China;
Beijing Inst Technol Sch Automat Beijing 100811 Peoples R China;
Trajectory; Atmospheric modeling; Real-time systems; Planning; Aerodynamics; Neural networks; Deep neural network (DNN); hypersonic vehicle (HV); multiobjective; real-time trajectory planning; real-time applicability;
机译:超音速再入车辆令人满意的确定性和概率约束的轨迹规划
机译:高超音速飞行器折返轨迹规划研究进展
机译:超音速车辆再入轨迹规划的进展
机译:基于深度神经网络的实时轨迹规划,用于障碍的自动导向车辆
机译:使用深卷积神经网络进行实时视觉检测和跟踪框架用于微空气车辆
机译:通过卷积神经网络优化车辆边界盒来确定车辆轨迹
机译:使用模糊令人满意的目标规划方法重新进入超音速车辆的轨迹优化