A Genetic Algorithm-Inspired UUV Path Planner Based on Dynamic Programming

Cheng, Chi‐Tsun; Fallahi, Kia; Leung, Henry; Tse, Chi Kong

doi:10.1109/tsmcc.2011.2180526

Cited by 48 publications

(26 citation statements)

References 10 publications

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“…In addition, evolutionary algorithms could also cope with large dimension problems and are able to provide a robust solution, without significant increase in the computational cost, while the search space complexity increases. Cheng et al [5] attempted to merge the benefits of a genetic algorithm (GA) with the fast results of a dynamic programming (DP) algorithm in order to solve the motion planning problem, for a 3-dof unmanned underwater vehicle (UUV). Alvarez et al [6] used a GA to determine the optimum path for an AUV in a strong current environment, whereas Sun and Zhang in [7], have considered the ocean currents in the global motion planning for a AUV, using also GA. Apart from a GA, in [8] the authors studied the use of other metaheuristic methods like Particle Swarm Optimization and Ant Colonization.…”

Section: Motion Planning For Uvmsmentioning

confidence: 99%

Rapid motion planning algorithm for optimal UVMS interventions in semi-structured environments using GPUs

Sotiropoulos

Kolonias

Housos

2015

Robotics and Autonomous Systems

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Section: Motion Planning For Uvmsmentioning

confidence: 99%

Rapid motion planning algorithm for optimal UVMS interventions in semi-structured environments using GPUs

Sotiropoulos

Kolonias

Housos

2015

Robotics and Autonomous Systems

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“…The base of the terrain is defined as a 100 × 100 m 2 square-shaped grid map. Similar terrain representations have been previously used in mobile robot path planning applications [19]- [21].…”

Section: A Terrain Representationmentioning

confidence: 99%

Finding energy-efficient paths on uneven terrains

Ganganath

Cheng

Tse

2014

2014 10th France-Japan/ 8th Europe-Asia Congress on Mecatronics (MECATRONICS2014- Tokyo)

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Abstract-Mobile robots are increasingly getting popular in outdoor applications. Long period of continuous operations are common in such applications. Therefore, robot motions need to be optimized to minimize their energy consumption. Shortest paths do not always guarantee minimum energy consumptions of mobile robots. This paper proposes a novel algorithm to generate energyefficient paths on uneven terrains using an established energycost model for mobile robots. Terrains are represented using grid based elevation maps. Similar to A* algorithm, the energy-cost of traversing through a particular gird depends on a heuristic energy-cost estimation from the current location to the goal. The proposed heuristic energy-cost function makes it possible to generate zigzag-like path patterns on steep hills under the power limitations of the robot. Therefore, the proposed method can find physically feasible energy-efficient paths on any given terrain, provided that such paths exist. Simulation results presented in this paper demonstrate the performance of the proposed algorithm on uneven terrains maps.

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“…The optimal solution or a set of globally optimal solutions minimises or maximises the objective function. The path finding problem is typically defined in terms of the Travelling Salesman Problem (TSP) [7] or a more general Vehicle Routing Problem (VRP) [4]. Determining the optimal solution is an NP-hard problem, so the size of problems that can be solved optimally is limited [3].…”

Section: Introductionmentioning

confidence: 99%