scholarly journals A Composite Metric Routing Approach for Energy-Efficient Shortest Path Planning on Natural Terrains

2021 ◽  
Vol 11 (15) ◽  
pp. 6939
Author(s):  
Mohamed Saad ◽  
Ahmed I. Salameh ◽  
Saeed Abdallah ◽  
Ali El-Moursy ◽  
Chi-Tsun Cheng
Keyword(s):  
Energy Consumption ◽  
Path Planning ◽  
Shortest Path ◽  
Energy Cost ◽  
Energy Efficient ◽  
Cost Minimization ◽  
Running Time ◽  
Path Distance ◽  
Planning Algorithm ◽  
Path Planning Algorithm

This paper explores the problem of energy-efficient shortest path planning on off-road, natural, real-life terrain for unmanned ground vehicles (UGVs). We present a greedy path planning algorithm based on a composite metric routing approach that combines the energy consumption and distance of the path. In our work, we consider the Terramechanics between the UGV and the terrain soil to account for the wheel sinkage effect, in addition to the terrain slope and soil deformation limitations in the development of the path planning algorithm. As benchmarks for comparison, we use a recent energy-cost minimization approach, in addition to an ant colony optimization (ACO) implementation. Our results indicate that the proposed composite metric routing approach outperforms the state-of-the-art energy-cost minimization method in terms of the resulting path distance, with a negligible increase in energy consumption. Moreover, our results indicate also that the proposed greedy algorithm strongly outperforms the ACO implementation in terms of the quality of the paths obtained and the algorithm running time. In fact, the running time of our proposed algorithm indicates its suitability for large natural terrain graphs with thousands of nodes and tens of thousands of links.

scholarly journals An energy-efficient path planning algorithm for unmanned surface vehicles

2018 ◽  
Vol 161 ◽  
pp. 308-321 ◽  
Author(s):  
Hanlin Niu ◽  
Yu Lu ◽  
Al Savvaris ◽  
Antonios Tsourdos
Keyword(s):  
Path Planning ◽  
Energy Efficient ◽  
Unmanned Surface Vehicles ◽  
Planning Algorithm ◽  
Path Planning Algorithm

scholarly journals Improved Path Planning and Attitude Control Method for Agile Maneuver Satellite with Double-Gimbal Control Moment Gyros

2015 ◽  
Vol 2015 ◽  
pp. 1-11
Author(s):  
Peiling Cui ◽  
Jingxian He ◽  
Jian Cui ◽  
Haitao Li
Keyword(s):  
Energy Consumption ◽  
Path Planning ◽  
Fourier Coefficients ◽  
Feedback Controller ◽  
Fourier Basis ◽  
Control Moment ◽  
Attitude Maneuver ◽  
Attitude Tracking ◽  
Planning Algorithm ◽  
Path Planning Algorithm

Double-gimbal control moment gyros can implement the satellite attitude maneuver efficiently. In order to reduce the energy consumption of double-gimbal control moment gyros and avoid the singularity state, an attitude maneuver path planning method is proposed by using the improved Fourier basis algorithm. Considering that the choice of the Fourier coefficients is important for the Fourier basis algorithm to converge quickly, a choosing method of the initial Fourier coefficients which can reduce the computational time of the path planning algorithm notably is proposed. Moreover, an attitude-tracking feedback controller based on the Fourier basis path planning algorithm is designed to acquire robustness. Simulation results show that the proposed path planning algorithm can implement attitude maneuver path planning in shortened time. Meanwhile, the feasibility of the attitude-tracking feedback controller which is based on the above path planning algorithm is verified in terms of the low energy consumption, high attitude-tracking precision, and the safe use of double-gimbal control moment gyros.

scholarly journals Any-Angle Path Planning

AI Magazine ◽  
2013 ◽  
Vol 34 (4) ◽  
pp. 85-107 ◽  
Author(s):  
Alex Nash ◽  
Sven Koenig
Keyword(s):  
Video Games ◽  
Path Planning ◽  
Shortest Path ◽  
Grid Cells ◽  
Grid Graph ◽  
Planning Algorithm ◽  
Planning Algorithms ◽  
Planning Methodology ◽  
Path Planning Algorithm

In robotics and video games, one often discretizes continuous terrain into a grid with blocked and unblocked grid cells and then uses path-planning algorithms to find a shortest path on the resulting grid graph. This path, however, is typically not a shortest path in the continuous terrain. In this overview article, we discuss a path-planning methodology for quickly finding paths in continuous terrain that are typically shorter than shortest grid paths. Any-angle path-planning algorithms are variants of the heuristic path-planning algorithm A* that find short paths by propagating information along grid edges (like A*, to be fast) without constraining the resulting paths to grid edges (unlike A*, to find short paths).

scholarly journals Tide-Inspired Path Planning Algorithm for Autonomous Vehicles

2021 ◽  
Vol 13 (22) ◽  
pp. 4644
Author(s):  
Heba Kurdi ◽  
Shaden Almuhalhel ◽  
Hebah Elgibreen ◽  
Hajar Qahmash ◽  
Bayan Albatati ◽  
...  
Keyword(s):  
Path Planning ◽  
Shortest Path ◽  
Execution Time ◽  
Autonomous Vehicles ◽  
The Moon ◽  
Breadth First Search ◽  
The Earth ◽  
Planning Algorithm ◽  
Np Hard Problem ◽  
Path Planning Algorithm

With the extensive developments in autonomous vehicles (AV) and the increase of interest in artificial intelligence (AI), path planning is becoming a focal area of research. However, path planning is an NP-hard problem and its execution time and complexity are major concerns when searching for optimal solutions. Thus, the optimal trade-off between the shortest path and computing resources must be found. This paper introduces a path planning algorithm, tide path planning (TPP), which is inspired by the natural tide phenomenon. The idea of the gravitational attraction between the Earth and the Moon is adopted to avoid searching blocked routes and to find a shortest path. Benchmarking the performance of the proposed algorithm against rival path planning algorithms, such as A*, breadth-first search (BFS), Dijkstra, and genetic algorithms (GA), revealed that the proposed TPP algorithm succeeded in finding a shortest path while visiting the least number of cells and showed the fastest execution time under different settings of environment size and obstacle ratios.

scholarly journals Human experience–inspired path planning for robots

2018 ◽  
Vol 15 (1) ◽  
pp. 172988141875704 ◽  
Author(s):  
Wenyong Gong ◽  
Xiaohua Xie ◽  
Yong-Jin Liu
Keyword(s):  
Path Planning ◽  
Energy Function ◽  
Optimal Path ◽  
Human Experience ◽  
Service Robots ◽  
A Algorithm ◽  
Slowing Down ◽  
Path Distance ◽  
Planning Algorithm ◽  
Path Planning Algorithm

In this article, we present a human experience–inspired path planning algorithm for service robots. In addition to considering the path distance and smoothness, we emphasize the safety of robot navigation. Specifically, we build a speed field in accordance with several human driving experiences, like slowing down or detouring at a narrow aisle, and keeping a safe distance to the obstacles. Based on this speed field, the path curvatures, path distance, and steering speed are all integrated to form an energy function, which can be efficiently solved by the A* algorithm to seek the optimal path by resorting to an admissible heuristic function estimated from the energy function. Moreover, a simple yet effective fast path smoothing algorithm is proposed so as to ease the robots steering. Several examples are presented, demonstrating the effectiveness of our human experience–inspired path planning method.

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