水下爬行机器人多目标路径规划的研究
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摘要
文章提出使用一种基于三角网格的fast marching(TFM)算法解决水下爬行机器人在2.5维水底地表环境下的路径规划问题,在制定规划算法的费用函数时,考虑了地形特征因素、水下爬行机器人的运动限制、任务本身要求等多个目标的决策和限制。通过仿真实验,验证了该算法在2.5维复杂水底地表环境下可以生成一条连续、平滑、最优的路径,并且可以根据不同的任务目标规划出满足任务要求的最优路径。蒙特卡罗实验表明,该算法运行速度非常快,可以进行在线规划。
In this paper, a fast marching algorithm based on triangular grid(TFM) was used to resolve underwater climbing robot path planning problem on 2.5-dimensional complex underwater surface. The cost function for this planning algorithm considered the decisions and constraints for multi-factors, such as the topography factors, the movement characteristics of underwater climbing robots and the tasks. The simulations verified that the proposed algorithm could generate a continuous, smooth and optimal path on 2.5-dimensional complex underwater surface, and it also could generate the optimal path which met the requirements of the tasks. The Monte Carlo simulation showed that the algorithm ran fast, and it could work for online planning.
In this paper, a fast marching algorithm based on triangular grid(TFM) was used to resolve underwater climbing robot path planning problem on 2.5-dimensional complex underwater surface. The cost function for this planning algorithm considered the decisions and constraints for multi-factors, such as the topography factors, the movement characteristics of underwater climbing robots and the tasks. The simulations verified that the proposed algorithm could generate a continuous, smooth and optimal path on 2.5-dimensional complex underwater surface, and it also could generate the optimal path which met the requirements of the tasks. The Monte Carlo simulation showed that the algorithm ran fast, and it could work for online planning.
引文
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[2]TEDESCHI F,CARBONE G.Design issues for hexapod walking robots[J].Robotics,2014,3(2):181-206.
[3]史美萍,吴军,李焱,等.移动机器人路径规划技术的研究现状与展望[J].国防科技大学学报,2006,28(5):104-108.
[4]LOZANO-PEREZ T.Automatic planning of manipulator transfer movements[J].IEEE Transactions on Systems Man and Cybernetics,1981,11(10):681-698.
[5]BROOKS R.New approaches to robotics[J].Science,1991,253(5025):1227-1232.
[6]CHOSET H,BURDICK J.Sensor based planning.I.The generalized Voronoi graph[C]//Proceedings of IEEE International Conference on Robotics and Automation.[S.l.]:IEEE,1995:1649-1655.
[7]LIU Y H,ARIMOTO S.Computation of the tangent graph of polygonal obstacles by moving-line processing[J].IEEETransactions on Robotics and Automation,1994,10(6):823-830.
[8]GERAERTS R,OVERMARS M H.A comparative study of probabilistic roadmap planners[M]//Algorithmic Foundations of Robotics V.Heidelberg:Springer,2004:43-58.
[9]ELFES A.Using occupancy grids for mobile robot perception and navigation[J].Computer,1989,22(6):46-57.
[10]罗柏文.深海钴结壳采集之微地形探测技术(浅水实验阶段)研究[D].长沙:中南大学,2008.
[11]KIMMEL R,SETHIAN J A.Computing geodesic paths on manifolds[J].Proceedings of the National Academy of Sciences,1998,95(15):8431-8435.
[12]BARTH T J,SETHIAN J A.Numerical schemes for the Hamilton-Jacobi and level set equations on triangulated domains[J].Journal of Computational Physics,1998,145(1):1-40.
[13]GARRIDO S,MALFAZ M,BLANCO D.Application of the fast marching method for outdoor motion planning in robotics[J].Robotics and Autonomous Systems,2013,61(2):106-114.
[14]SETHIAN J A.Level set methods and fast marching methods:evolving interfaces in computational geometry,fluid mechanics,computer vision,and materials science[M].Cambrideg,Eng.:Cambridge University Press,1999.
[15]CASTEJON C,BOADA B L,BLANCO D,et al.Traversable region modeling for outdoor navigation[J].Journal of Intelligent and Robotic Systems,2005,43(2/3/4):175-216.
[16]OLSEN J.Realtime procedural terrain generation[D].Odense:University Southern Denmark,2004.
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