Multiple-Objective Motion Planning for Unmanned Aerial Vehicles

被引:0
|
作者
Scherer, Sebastian [1 ]
Singh, Sanjiv [1 ]
机构
[1] Carnegie Mellon Univ, Inst Robot, Pittsburgh, PA 15213 USA
来源
2011 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS | 2011年
关键词
FRAMEWORK;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Here we consider the problem of low-flying rotor-craft that must perform various missions such as navigating to specific goal points while avoiding obstacles, looking for acceptable landing sites or performing continuous surveillance. Not all of such missions can be expressed as safe, goal seeking, partly because in many cases there isn't an obvious goal. Rather than developing singular solutions to each mission, we seek a generalized formulation that enables us to express a wider range of missions. Here we propose a framework that allows for multiple objectives to be considered simultaneously and discuss corresponding planning algorithms that are capable of running in realtime on autonomous air vehicles. The algorithms create a set of initial hypotheses that are then optimized by a sub-gradient based trajectory algorithm that optimizes the multiple objectives, producing dynamically feasible trajectories. We have demonstrated the feasibility of our approach with changing cost functions based on newly discovered information. We report on results in simulation of a system that is tasked with navigating safely between obstacles while searching for an acceptable landing site.
引用
收藏
页数:8
相关论文
共 50 条
  • [31] Velocity field path-planning for single and multiple unmanned aerial vehicles
    McInnes, CR
    AERONAUTICAL JOURNAL, 2003, 107 (1073): : 419 - 426
  • [32] Geofencing Motion Planning for Unmanned Aerial Vehicles Using an Anticipatory Range Control Algorithm
    Thomas, Peter R.
    Sarhadi, Pouria
    Astolfi, Davide
    Chen, Zheng
    MACHINES, 2024, 12 (01)
  • [33] Hybrid Optimization Based Multi-Objective Path Planning Framework for Unmanned Aerial Vehicles
    Ajith, V. S.
    Jolly, K. G.
    CYBERNETICS AND SYSTEMS, 2023, 54 (08) : 1397 - 1423
  • [34] Control Platform for Multiple Unmanned Aerial Vehicles
    Zacarias, Iulisloi
    Leite, Carlos E. T.
    Schwarzrock, Janana
    de Freitas, Edison P.
    IFAC PAPERSONLINE, 2016, 49 (30): : 36 - 41
  • [35] Motion control problems for multimode unmanned aerial vehicles
    A. S. Syrov
    A. M. Puchkov
    V. Yu. Rutkovskii
    V. M. Glumov
    Automation and Remote Control, 2017, 78 : 1128 - 1137
  • [36] Motion control problems for multimode unmanned aerial vehicles
    Syrov, A. S.
    Puchkov, A. M.
    Rutkovskii, V. Yu.
    Glumov, V. M.
    AUTOMATION AND REMOTE CONTROL, 2017, 78 (06) : 1128 - 1137
  • [37] Task assignment and path planning for distributed multiple unmanned aerial vehicles in the last mile
    Guo, Xinghai
    Ji, Mingjun
    Wen, Dusu
    Zhang, Xin
    Tian, Shuang
    Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice, 2021, 41 (04): : 946 - 961
  • [38] Path planning in unmanned aerial vehicles: An optimistic overview
    Shahid, Noor
    Abrar, Muhammad
    Ajmal, Ushna
    Masroor, Roha
    Amjad, Shehzad
    Jeelani, Mubashir
    INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, 2022, 35 (06)
  • [39] Survey on Coverage Path Planning with Unmanned Aerial Vehicles
    Cabreira, Taua M.
    Brisolara, Lisane B.
    Paulo R., Ferreira Jr.
    DRONES, 2019, 3 (01) : 1 - 38
  • [40] Coverage path planning for multiple unmanned aerial vehicles in maritime search and rescue operations
    Cho, Sung Won
    Park, Hyun Ji
    Lee, Hanseob
    Shim, David Hyunchul
    Kim, Sun-Young
    COMPUTERS & INDUSTRIAL ENGINEERING, 2021, 161