During the use of robotics in applications such as antiterrorism or combat,a motion-constrained pursuer vehicle,such as a Dubins unmanned surface vehicle(USV),must get close enough(within a prescribed zero or positive...During the use of robotics in applications such as antiterrorism or combat,a motion-constrained pursuer vehicle,such as a Dubins unmanned surface vehicle(USV),must get close enough(within a prescribed zero or positive distance)to a moving target as quickly as possible,resulting in the extended minimum-time intercept problem(EMTIP).Existing research has primarily focused on the zero-distance intercept problem,MTIP,establishing the necessary or sufficient conditions for MTIP optimality,and utilizing analytic algorithms,such as root-finding algorithms,to calculate the optimal solutions.However,these approaches depend heavily on the properties of the analytic algorithm,making them inapplicable when problem settings change,such as in the case of a positive effective range or complicated target motions outside uniform rectilinear motion.In this study,an approach employing a high-accuracy and quality-guaranteed mixed-integer piecewise-linear program(QG-PWL)is proposed for the EMTIP.This program can accommodate different effective interception ranges and complicated target motions(variable velocity or complicated trajectories).The high accuracy and quality guarantees of QG-PWL originate from elegant strategies such as piecewise linearization and other developed operation strategies.The approximate error in the intercept path length is proved to be bounded to h^(2)/(4√2),where h is the piecewise length.展开更多
0引言随着内河航运向智能化、无人化转型,船舶自主避障路径规划成为突破行业发展瓶颈的关键议题。内河航道环境的复杂性,对传统感知与导航技术提出严峻挑战。图像识别凭借其在环境信息解析方面的优势,即时定位与地图构建(Simultaneous L...0引言随着内河航运向智能化、无人化转型,船舶自主避障路径规划成为突破行业发展瓶颈的关键议题。内河航道环境的复杂性,对传统感知与导航技术提出严峻挑战。图像识别凭借其在环境信息解析方面的优势,即时定位与地图构建(Simultaneous Localization and Mapping,SLAM)技术则依托实时建图与定位能力,二者的深度融合为智能船舶内河航道自主避障提供了核心支撑。如何借助技术协作打破单一传感器的限制,实现在复杂情境里精准认知环境、高效制定路径决策以及可靠保障安全,不仅是技术领域的创新课题,也是促进内河航运提效、保障航行安全的关键探索途径。展开更多
基金supported by the National Natural Sci‐ence Foundation of China(Grant No.62306325)。
文摘During the use of robotics in applications such as antiterrorism or combat,a motion-constrained pursuer vehicle,such as a Dubins unmanned surface vehicle(USV),must get close enough(within a prescribed zero or positive distance)to a moving target as quickly as possible,resulting in the extended minimum-time intercept problem(EMTIP).Existing research has primarily focused on the zero-distance intercept problem,MTIP,establishing the necessary or sufficient conditions for MTIP optimality,and utilizing analytic algorithms,such as root-finding algorithms,to calculate the optimal solutions.However,these approaches depend heavily on the properties of the analytic algorithm,making them inapplicable when problem settings change,such as in the case of a positive effective range or complicated target motions outside uniform rectilinear motion.In this study,an approach employing a high-accuracy and quality-guaranteed mixed-integer piecewise-linear program(QG-PWL)is proposed for the EMTIP.This program can accommodate different effective interception ranges and complicated target motions(variable velocity or complicated trajectories).The high accuracy and quality guarantees of QG-PWL originate from elegant strategies such as piecewise linearization and other developed operation strategies.The approximate error in the intercept path length is proved to be bounded to h^(2)/(4√2),where h is the piecewise length.
文摘0引言随着内河航运向智能化、无人化转型,船舶自主避障路径规划成为突破行业发展瓶颈的关键议题。内河航道环境的复杂性,对传统感知与导航技术提出严峻挑战。图像识别凭借其在环境信息解析方面的优势,即时定位与地图构建(Simultaneous Localization and Mapping,SLAM)技术则依托实时建图与定位能力,二者的深度融合为智能船舶内河航道自主避障提供了核心支撑。如何借助技术协作打破单一传感器的限制,实现在复杂情境里精准认知环境、高效制定路径决策以及可靠保障安全,不仅是技术领域的创新课题,也是促进内河航运提效、保障航行安全的关键探索途径。
