Robot Technology component implementation of the simultaneous path planning and topological mapping algorithm

2013 ◽  
Author(s):  
Songmin Jia ◽  
Xiongwei Pang ◽  
Bing Guo
Keyword(s):  
Path Planning ◽  
Mapping Algorithm ◽  
Topological Mapping ◽  
Robot Technology

scholarly journals A Hybrid Path-Planning Strategy for Mobile Robots with Limited Sensor Capabilities

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1049 ◽  
Author(s):  
Guilherme de Oliveira ◽  
Kevin de Carvalho ◽  
Alexandre Brandão
Keyword(s):  
Path Planning ◽  
Avoidance Task ◽  
Planning Problem ◽  
Local Planning ◽  
Mapping Algorithm ◽  
Planning Strategy ◽  
Algorithm Efficiency ◽  
Cost Efficient ◽  
Environment Experiment ◽  
Path Planner

This paper introduces a strategy for the path planning problem for platforms with limited sensor and processing capabilities. The proposed algorithm does not require any prior information but assumes that a mapping algorithm is used. If enough information is available, a global path planner finds sub-optimal collision-free paths within the known map. For the real time obstacle avoidance task, a simple and cost-efficient local planner is used, making the algorithm a hybrid global and local planning solution. The strategy was tested in a real, cluttered environment experiment using the Pioneer P3-DX and the Xbox 360 kinect sensor, to validate and evaluate the algorithm efficiency.

Simultaneous Path Planning and Topological Mapping (SP2ATM) for environment exploration and goal oriented navigation

2011 ◽  
Vol 59 (3-4) ◽  
pp. 228-242 ◽  
Author(s):  
Shuzhi Sam Ge ◽  
Qun Zhang ◽  
Aswin Thomas Abraham ◽  
Brice Rebsamen
Keyword(s):  
Path Planning ◽  
Topological Mapping ◽  
Environment Exploration

Path Planning for Mobile Robot Based on ACA-GA

2011 ◽  
Vol 135-136 ◽  
pp. 673-677
Author(s):  
Li Xun Zhang ◽  
Yin Xue Wang ◽  
Bing Bing Wang ◽  
Qian Deng ◽  
Hao Chen
Keyword(s):  
Genetic Algorithm ◽  
Path Planning ◽  
Mobile Robot ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Optimal Paths ◽  
Global Path Planning ◽  
Crossover Rate ◽  
Robot Technology ◽  
Technology Area

Path planning for mobile robot is a kernel problem in the robot technology area, with the characteristics of complexity, binding and nonlinearity. On account of global path planning for mobile robot in static environment, this paper discussed a method of combining ant colony algorithm and genetic algorithm. After completing a cycle of ant colony algorithm, two paths ants walked were randomly selected, and these two paths were further optimized genetically on the basis of certain crossover rate, if more optimal paths were obtained, the pheromone would be released in the more optimal paths, by this method the diversity of solution could be increased and solution speed be improved. The simulation result has verified the effectiveness of the proposed method.

scholarly journals Ellipsoidal Path Planning for Unmanned Aerial Vehicles

2021 ◽  
Vol 11 (17) ◽  
pp. 7997
Author(s):  
Carlos Villaseñor ◽  
Alberto A. Gallegos ◽  
Gehova Lopez-Gonzalez ◽  
Javier Gomez-Avila ◽  
Jesus Hernandez-Barragan ◽  
...  
Keyword(s):  
Path Planning ◽  
Unmanned Aerial Vehicles ◽  
Clustering Algorithms ◽  
Computational Cost ◽  
Mapping Algorithm ◽  
Planning Strategy ◽  
Aerial Vehicles ◽  
Planning Algorithm ◽  
Trained Neural Network ◽  
Path Planning Algorithm

The research in path planning for unmanned aerial vehicles (UAV) is an active topic nowadays. The path planning strategy highly depends on the map abstraction available. In a previous work, we presented an ellipsoidal mapping algorithm (EMA) that was designed using covariance ellipsoids and clustering algorithms. The EMA computes compact in-memory maps, but still with enough information to accurately represent the environment and to be useful for robot navigation algorithms. In this work, we develop a novel path planning algorithm based on a bio-inspired algorithm for navigation in the ellipsoidal map. Our approach overcomes the problem that there is no closed formula to calculate the distance between two ellipsoidal surfaces, so it was approximated using a trained neural network. The presented path planning algorithm takes advantage of ellipsoid entities to represent obstacles and compute paths for small UAVs regardless of the concavity of these obstacles, in a very geometrically explicit way. Furthermore, our method can also be used to plan routes in dynamical environments without adding any computational cost.

Research on Path Planning for Mobile Robot Based on Grid and Hybrid of GA/SA

2012 ◽  
Vol 479-481 ◽  
pp. 1499-1503 ◽  
Author(s):  
Wen Jun Yang ◽  
Huai Bin Wang ◽  
Jing Hui Wang
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Grid Method ◽  
Environmental Modeling ◽  
Planning Problem ◽  
Mutation Probability ◽  
Robot Technology ◽  
Crossover And Mutation ◽  
Path Planning Problem ◽  
Technology Area

Path planning is the kernel problem of the robot technology area. In this paper, the grid method is used to make environmental modeling, Since the Genetic Algorithm (GA) has its immanent limitations and the Simulated Annealing (SA) Algorithm has the advantages in some aspects, combined these two algorithms together just achieve the perfection. In view of this, a hybrid of GA and SA (GA-SA Hybrid) is proposed in this paper to solve path planning problem for mobile robot. The algorithm making the crossover and mutation probability adjusted adaptively and nonlinearly with the completion time, can avoid such disadvantages as premature convergence. The new algorithm has better capability of searching globally and locally. The simulation results demonstrate that the proposed algorithm is valid and effective.

scholarly journals A Corporative System of Edge Mapping and Hybrid Path A*-Douglas-Pucker Algorithm Planning Method

2019 ◽  
Vol 54 (5) ◽  
Author(s):  
Wahab K. Yousif ◽  
Ahmed A. Ali
Keyword(s):  
Path Planning ◽  
Detection Algorithm ◽  
Computational Time ◽  
Mapping Algorithm ◽  
Starting Point ◽  
Mapping Process ◽  
Planning Algorithm ◽  
Canny Edge ◽  
Path Planning Algorithm ◽  
Canny Edge Detection Algorithm

This paper proposes a corporative system of the edge mapping and hybrid path planning. The mapping process is predicated on modified canny edge detection algorithm. The presented mapping algorithm is found to be adaptable to various scenarios; it is tested on several cases to extract the impediments as well as the constrained region of the map. The generated map is a 2D edge map that contains the information about starting point, goal and obstacles. After that, the outcome of the edge map is processed in path planning algorithm in order to identify the optimum path. The proposed path planning is a hybrid A*-Douglas pucker algorithm. The presented path planning algorithm is reduced the set points and computational time.

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