Path Planning Techniques for Mobile Robots A Review

Campbell, Sean; Mahony, Niall O’; Carvalho, Anderson; Krpálková, Lenka; Riordan, Daniel; Walsh, Joseph T.

doi:10.1109/icmre49073.2020.9065187

Cited by 62 publications

(58 citation statements)

References 23 publications

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“…The Bug algorithms, Bug1 and Bug2, make the robot circumvent any obstacle found on its way until it reaches the goal [ 86 ]. The main difference between them is that Bug1 makes the robot drive the full boundary of any obstacle (see Figure 6 a), whereas Bug2 can drive it only partially [ 19 ]. They despise optimality in favour of easiness in the implementation and very minimal computation.…”

Section: Reactive-computing-based Path Planning Algorithmsmentioning

confidence: 99%

Path Planning for Autonomous Mobile Robots: A Review

Sánchez‐Ibáñez

Pérez-del-Pulgar

García-Cerezo

2021

Sensors

202

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Providing mobile robots with autonomous capabilities is advantageous. It allows one to dispense with the intervention of human operators, which may prove beneficial in economic and safety terms. Autonomy requires, in most cases, the use of path planners that enable the robot to deliberate about how to move from its location at one moment to another. Looking for the most appropriate path planning algorithm according to the requirements imposed by users can be challenging, given the overwhelming number of approaches that exist in the literature. Moreover, the past review works analyzed here cover only some of these approaches, missing important ones. For this reason, our paper aims to serve as a starting point for a clear and comprehensive overview of the research to date. It introduces a global classification of path planning algorithms, with a focus on those approaches used along with autonomous ground vehicles, but is also extendable to other robots moving on surfaces, such as autonomous boats. Moreover, the models used to represent the environment, together with the robot mobility and dynamics, are also addressed from the perspective of path planning. Each of the path planning categories presented in the classification is disclosed and analyzed, and a discussion about their applicability is added at the end.

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Section: Reactive-computing-based Path Planning Algorithmsmentioning

confidence: 99%

Path Planning for Autonomous Mobile Robots: A Review

Sánchez‐Ibáñez

Pérez-del-Pulgar

García-Cerezo

2021

Sensors

202

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“…First, the barrier cells are split into two new cells, then the pure cells (non-blocking cells) are added to the sequence. [29] using Global path planning. Figure 5 shows the cell decomposition method.…”

Section:  Cell Decomposition (Cd)mentioning

confidence: 99%

“…Borenstein and Koren initially introduced this method and considered it to be an improved version of the PF method. VFH is an approach to prevent obstacles in real-time, which enables a robot to identify and avoid unknown obstacles while continuing to pursue the goal [29]. Chen et al in 2019 [26] are present a local path planning method based on VFH* the drawback did not find the optimal path.…”

Section:  Vector Field Histogrammentioning

confidence: 99%

A Review on Path Planning Algorithms for Mobile Robots

Abed¹,

Lutfy²,

Al-Doori³

2021

ETJ

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Mobile robots use is rising every day. Path planning algorithms are needed to make a traveler of robots with the least cost and without collisions. Many techniques have been developed in path planning for mobile robot worldwide, however, the most commonly used techniques are presented here for further study. This essay aims to review various path planning strategies for mobile robots using different optimization methods taken recent publisher’s paper in last five year.

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“…The related literature review is presented in [ 31 ]. It shows that the main area of focus of previous studies was the determination of optimal routes for the movement of autonomous robots (UGV—Unmanned Ground Vehicle) [ 32 ]. The authors of [ 33 ] used aviation photography for this purpose.…”

Section: Introductionmentioning

confidence: 99%

Methodology of Using Terrain Passability Maps for Planning the Movement of Troops and Navigation of Unmanned Ground Vehicles

Dawid

Pokonieczny

2021

Sensors

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The determination of the route of movement is a key factor which enables navigation. In this article, the authors present the methodology of using different resolution terrain passability maps to generate graphs, which allow for the determination of the optimal route between two points. The routes are generated with the use of two commonly used pathfinding algorithms: Dijkstra’s and A-star. The proposed methodology allows for the determination of routes in various variants—a more secure route that avoids all terrain obstacles with a wide curve, or a shorter route, which is, however, more difficult to pass. In order to achieve that, two functions that modify the value of the index of passability (IOP), which is assigned to the primary fields that the passability map consists of, have been used. These functions have a β parameter that augments or reduces the impact of the applied function on IOP values. The paper also shows the possibilities of implementation of the methodology for the movement of single vehicles or unmanned ground vehicles (UGVs) by using detailed maps as well as for determining routes for large military operational units moving in a 1 km wide corridor. The obtained results show that the change in β value causes the change of a course of the route as expected and that Dijkstra’s algorithm is more stable and slightly faster than A-star. The area of application of the presented methodology is very wide because, except for planning the movement of unmanned ground vehicles or military units of different sizes, it can be used in crisis management, where the possibility of reaching the area outside the road network can be of key importance for the success of the salvage operation.

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Path Planning Techniques for Mobile Robots A Review

Cited by 62 publications

References 23 publications

Path Planning for Autonomous Mobile Robots: A Review

Path Planning for Autonomous Mobile Robots: A Review

A Review on Path Planning Algorithms for Mobile Robots

Methodology of Using Terrain Passability Maps for Planning the Movement of Troops and Navigation of Unmanned Ground Vehicles

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