Real-time Motion-planning of Curvature-constrained AUVs under Steady Ocean Currents

被引:0
作者
Mittal, Khushboo [1 ]
Song, Junnan [1 ]
Gupta, Shalabh [1 ]
机构
[1] Univ Connecticut, Dept Elect & Comp Engn, Storrs, CT 06269 USA
来源
OCEANS 2019 MTS/IEEE SEATTLE | 2019年
关键词
Dubins paths; motion planning; curvature constrained vehicles; AUVs; ocean currents; AUTONOMOUS UNDERWATER VEHICLES; OPTIMAL TRAJECTORY GENERATION; PATH; ASTERISK;
D O I
暂无
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
In this paper, we propose a novel approach to obtain a real-time solution for the minimum-time motion-planning problem for curvature-constrained AUVs in the presence of ocean currents. The existing solution to this problem is obtained by solving the six Dubins path types (i.e., LSL, RSR, LSR, RSL, LRL and RLR) in the presence of currents, four of which involve a root-finding problem consisting of transcendental functions. Thus, the computational complexity of the exiting solution makes it infeasible for real-time applications, such as rapidly changing oceanic environments. The proposed approach utilizes only the LSL and RSR path types from the Dubins set, which provide analytical solutions as needed for real-time applications. It is shown that by extending the feasible range of circular arcs in these path types from 2 pi to 4 pi, full reachability is guarantee; i.e., a solution can be obtained for every pair of start and goal poses. Furthermore, it is shown that the proposed solution provides better time-costs with lower travel times as compared to the existing Dubins LSL and RSR paths. The proposed approach is validated by numerical studies through various examples to highlight its benefits for real-time applications.
引用
收藏
页数:6
相关论文
共 28 条
[1]   Evolutionary path planning for autonomous underwater vehicles in a variable ocean [J].
Alvarez, A ;
Caiti, A ;
Onken, R .
IEEE JOURNAL OF OCEANIC ENGINEERING, 2004, 29 (02) :418-429
[2]  
[Anonymous], 2006, Planning algorithms, Complexity
[3]   Optimal Synthesis of the Zermelo-Markov-Dubins Problem in a Constant Drift Field [J].
Bakolas, Efstathios ;
Tsiotras, Panagiotis .
JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS, 2013, 156 (02) :469-492
[5]  
Garau B, 2005, IEEE INT CONF ROBOT, P194
[6]  
Garau B, 2009, Journal of Maritime Research, V6, P5
[7]   Generalized Ising model for dynamic adaptation in autonomous systems [J].
Gupta, S. ;
Ray, A. ;
Phoha, S. .
EPL, 2009, 87 (01)
[8]   POSE: Prediction-Based Opportunistic Sensing for Energy Efficiency in Sensor Networks Using Distributed Supervisors [J].
Hare, James Z. ;
Gupta, Shalabh ;
Wettergren, Thomas A. .
IEEE TRANSACTIONS ON CYBERNETICS, 2018, 48 (07) :2114-2127
[9]   Optimal trajectory generation in ocean flows [J].
Inanc, T ;
Shadden, SC ;
Marsden, JE .
ACC: Proceedings of the 2005 American Control Conference, Vols 1-7, 2005, :674-679
[10]  
Koay TB, 2013, OCEANS-IEEE