A Comparative Study of Six Basic Approaches for Path Planning Towards an Autonomous Navigation

Randria, Iadaloharivola; Khelifa, Mohamed Moncef Ben; Bouchouicha, Moez; Abellard, Patrick

doi:10.1109/iecon.2007.4460164

Cited by 17 publications

(8 citation statements)

References 9 publications

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“…To the best of our knowledge, the only previous comparative study of exact and heuristic approaches is the study by Randria et al 4 In this article, six different approaches for the global path planning problem were evaluated: breadthfirst search, depth-first search, A Ã , Moore-Dijkstra, neural approach and GA. Three parameters were evaluated: the distance travelled by the robot, the number of visited waypoints and the computational time (with and without initialization). Simulation was conducted in four environments, and it was demonstrated that GA outperforms the other approaches in terms of distance and execution time.…”

Section: Comparative Studies Of Heuristic and Exact Approachesmentioning

confidence: 99%

Design and performance analysis of global path planning techniques for autonomous mobile robots in grid environments

Châari

Koubâa

Bennaceur

et al. 2017

International Journal of Advanced Robotic Systems

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This article presents the results of the 2-year iroboapp research project that aims at devising path planning algorithms for large grid maps with much faster execution times while tolerating very small slacks with respect to the optimal path. We investigated both exact and heuristic methods. We contributed with the design, analysis, evaluation, implementation and experimentation of several algorithms for grid map path planning for both exact and heuristic methods. We also designed an innovative algorithm called relaxed A-star that has linear complexity with relaxed constraints, which provides near-optimal solutions with an extremely reduced execution time as compared to A-star. We evaluated the performance of the different algorithms and concluded that relaxed A-star is the best path planner as it provides a good trade-off among all the metrics, but we noticed that heuristic methods have good features that can be exploited to improve the solution of the relaxed exact method. This led us to design new hybrid algorithms that combine our relaxed A-star with heuristic methods which improve the solution quality of relaxed A-star at the cost of slightly higher execution time, while remaining much faster than A Ã for large-scale problems. Finally, we demonstrate how to integrate the relaxed A-star algorithm in the robot operating system as a global path planner and show that it outperforms its default path planner with an execution time 38% faster on average.

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Section: Comparative Studies Of Heuristic and Exact Approachesmentioning

confidence: 99%

Design and performance analysis of global path planning techniques for autonomous mobile robots in grid environments

Châari

Koubâa

Bennaceur

et al. 2017

International Journal of Advanced Robotic Systems

View full text Add to dashboard Cite

show abstract

“…This increases the difficulty of achieving realtime performance on a computer. 7,8 The geometric feature map 9 was proposed by Nilsson in 1968. It is based on the polygon obstacle model.…”

Section: Representation Models Of the Indoor Environmentmentioning

confidence: 99%

“…There are many methods for achieving the construction of an indoor topological map, such as a thinning algorithm and hit-miss-transformation (HMT) or Delaunay method. 11,12 The generation of a threedimensional route 7 uses topology theory and a series of image-processing methods, including image thinning 13 and line-segment extraction from thinned hallways of single-pixel width. The Delaunay triangulation idea 11 calculates the road-network model from path points combined with an indoor location-information map.…”

Section: Representation Models Of the Indoor Environmentmentioning

confidence: 99%

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An improved searching algorithm for indoor trajectory reconstruction

Zhang

et al. 2017

International Journal of Distributed Sensor Networks

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Trajectory reconstruction of mobile targets in large-scale infrastructure enables events in a range of applications, such as regional security, tourism, and healthcare, to be visualized. However, indoor environmental factors complicate the reconstruction process, usually resulting in reduced efficiency. In this article, we propose a searching algorithm that aims at a reasonable trajectory reconstruction scheme. The algorithm is developed based on the branch-and-bound method, which incorporates both depth-first search and breadth-first search so that a fast trajectory reconstruction on a topological map becomes viable. Experimental results demonstrated that the considered strategies are effective in accelerating reconstruction through a performance evaluation against current approaches for trajectory reconstruction.

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“…To cope with a dynamic industrial environment, where obstacle presence can be very unpredictable, a real-time path planer was implemented [9]- [14].…”

Section: Introductionmentioning

confidence: 99%

Localization and Navigation of an Omnidirectional Mobile Robot: The Robot@Factory Case Study

Costa

Moreira

Campos

et al. 2016

IEEE R. Iberoamericana Tecnologias Aprendizaje

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Abstract-The Robot@Factory competition was recently included in Robotica, the main Portuguese Robotics Competition. This robot competition takes place in an emulated factory plant, where automatic guided vehicles (AGVs) must cooperate to perform tasks. To accomplish their goals, the AGVs must deal with localization, navigation, scheduling, and cooperation problems that must be solved autonomously. This robot competition can play an important role in education due to its inherent multidisciplinary approach, which can motivate students to bridge different technological areas. It can also play an important role in research and development, because it is expected that its outcomes will later be transferred to real-world problems in manufacturing or service robots. By presenting a scaled-down factory shop floor, this competition creates a benchmark that can be used to compare different approaches to the challenges that arise in this kind of environment. The ability to alter the environment, in some restricted areas, can usually promote the test and evaluation of different localization mechanisms, which is not possible in other competitions. This paper presents one of the possible approaches to build a robot capable of entering this competition. It can be used as a reference to current and new teams.

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A Comparative Study of Six Basic Approaches for Path Planning Towards an Autonomous Navigation

Cited by 17 publications

References 9 publications

Design and performance analysis of global path planning techniques for autonomous mobile robots in grid environments

Design and performance analysis of global path planning techniques for autonomous mobile robots in grid environments

An improved searching algorithm for indoor trajectory reconstruction

Localization and Navigation of an Omnidirectional Mobile Robot: The Robot@Factory Case Study

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