Terrain Based D∗ Algorithm for Path Planning

Saranya, C.; Unnikrishnan, Manju; Ali, S. Akbar; Sheela, D.S.; Lalithambika, V.R.

doi:10.1016/j.ifacol.2016.03.049

Cited by 42 publications

(22 citation statements)

References 7 publications

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“…A modified approach of D* for terrain-based path planning is proposed in [26]. Besides the distance to be travelled, the terrain slope estimate is also considered in the cost function computation to plan the path.…”

Section: D* Algorithmmentioning

confidence: 99%

Review on path planning algorithm for unmanned aerial vehicles

Ibrahim

Saparudin

2021

IJEECS

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The path planning problem has been a crucial topic to be solved in autonomous vehicles. Path planning consists operations to find the route that passes through all of the points of interest in a given area. Several algorithms have been proposed and outlined in the various literature for the path planning of autonomous vehicle especially for unmanned aerial vehicles (UAV). The algorithms are not guaranteed to give full performance in each path planning cases but each one of them has their own specification which makes them suitable in sophisticated situation. This review paper evaluates several possible different path planning approaches of UAVs in terms optimal path, probabilistic completeness and computation time along with their application in specific problems.

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Section: D* Algorithmmentioning

confidence: 99%

Review on path planning algorithm for unmanned aerial vehicles

Ibrahim

Saparudin

2021

IJEECS

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“…Current research focuses on the autonomous movement of vehicles in a dynamic environment, full of terrain obstacles [ 44 , 45 , 46 ]. Understandably, scientists pay special attention to considering obstacles caused by terrain formation, hence a large number of publications include Digital Terrain Models in the presented methodologies [ 47 , 48 , 49 , 50 ].…”

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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“…There has been some research into path planning in a geographical or terrainbased setting though most previous work is focused on discrete, graph-based methods employing Djikstra's algorithm and its many variants: so-called A * and D * algorithms [15,27]. Such methods have long been used for vehicular navigation and can be adapted to include real-time obstacle recognition [19].…”

Section: Introductionmentioning

confidence: 99%

Optimal human navigation in steep terrain: a Hamilton–Jacobi–Bellman approach

Parkinson

Arnold

Bertozzi

et al. 2019

Communications in Mathematical Sciences

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We present a method for determining optimal walking paths in steep terrain using the level set method and an optimal control formulation. By viewing the walking direction as a control variable, we can determine the optimal control by solving a Hamilton-Jacobi-Bellman equation. We then calculate the optimal walking path by solving an ordinary differential equation. We demonstrate the effectiveness of our method by computing optimal paths which travel throughout mountainous regions of Yosemite National Park. We include details regarding the numerical implementation of our model and address a specific application of a law enforcement agency patrolling a nationally protected area.

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Terrain Based D∗ Algorithm for Path Planning

Cited by 42 publications

References 7 publications

Review on path planning algorithm for unmanned aerial vehicles

Review on path planning algorithm for unmanned aerial vehicles

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

Optimal human navigation in steep terrain: a Hamilton–Jacobi–Bellman approach

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