scholarly journals Autonomous Robots Path Planning: An Adaptive Roadmap Approach

2013 ◽  
Vol 373-375 ◽  
pp. 246-254 ◽  
Author(s):  
Mohamed Elbanhawi ◽  
Milan Simic ◽  
Reza Jazar
Keyword(s):  
Computational Complexity ◽  
Path Planning ◽  
Autonomous Robots ◽  
Autonomous Mobile Robots ◽  
Current Position ◽  
Military Applications ◽  
Planning Methods ◽  
Planning Algorithm ◽  
Real Time Applications ◽  
Path Planning Algorithm

Developing algorithms that allow robots to independently navigate unknown environments is a widely researched area of robotics. The potential for autonomous mobile robots use, in industrial and military applications, is boundless. Path planning entails computing a collision free path from a robots current position to a desired target. The problem of path planning for these robots remains underdeveloped. Computational complexity, path optimization and robustness are some of the issues that arise. Current algorithms do not generate general solutions for different situations and require user experience and optimization. Classical algorithms are computationally extensive. This reduces the possibility of their use in real time applications. Additionally, classical algorithms do not allow for any control over attributes of the generated path. A new roadmap path planning algorithm is proposed in this paper. This method generates waypoints, through which the robot can avoid obstacles and reach its goal. At the heart of this algorithm is a method to control the distance of the waypoints from obstacles, without increasing its computational complexity. Several simulations were run to illustrate the robustness and adaptability of this approach, compared to the most commonly used path planning methods.

scholarly journals Efficient robotic path planning algorithm based on artificial potential field

2021 ◽  
Vol 11 (6) ◽  
pp. 4840
Author(s):  
Elia Nadira Sabudin ◽  
Rosli Omar ◽  
Sanjoy Kumar Debnath ◽  
Muhammad Suhaimi Sulong
Keyword(s):  
Computational Complexity ◽  
Path Planning ◽  
Potential Field ◽  
Path Length ◽  
Computation Time ◽  
Cell Decomposition ◽  
Target Point ◽  
Planning Methods ◽  
Planning Algorithm ◽  
Path Planning Algorithm

<span lang="EN-US">Path planning is crucial for a robot to be able to reach a target point safely to accomplish a given mission. In path planning, three essential criteria have to be considered namely path length, computational complexity and completeness. Among established path planning methods are voronoi diagram (VD), cell decomposition (CD), probability roadmap (PRM), visibility graph (VG) and potential field (PF). The above-mentioned methods could not fulfill all three criteria simultaneously which limits their application in optimal and real-time path planning. This paper proposes a path PF-based planning algorithm called dynamic artificial PF (DAPF). The proposed algorithm is capable of eliminating the local minima that frequently occurs in the conventional PF while fulfilling the criterion of path planning. DAPF also integrates path pruning to shorten the planned path. In order to evaluate its performance, DAPF has been simulated and compared with VG in terms of path length and computational complexity. It is found that DAPF is consistent in generating paths with low computation time in obstacle-rich environments compared to VG. The paths produced also are nearly optimal with respect to VG.</span>

scholarly journals Development and Implementation of Spline-based Path Planning Algorithm in ROS/Gazebo Environment

2019 ◽  
Vol 18 (1) ◽  
pp. 57-84 ◽  
Author(s):  
Lavrenov Lavrenov ◽  
Evgeni Magid ◽  
Matsuno Fumitoshi ◽  
Mikhail Svinin ◽  
Jackrit Suthakorn
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Cost Function ◽  
Working Environment ◽  
Autonomous Mobile Robots ◽  
Dynamic Tuning ◽  
Starting Point ◽  
Geometric Point ◽  
Planning Algorithm ◽  
Path Planning Algorithm

Path planning for autonomous mobile robots is an important task within robotics field. It is common to use one of the two classical approaches in path planning: a global approach when an entire map of a working environment is available for a robot or local methods, which require the robot to detect obstacles with a variety of onboard sensors as the robot traverses the environment. In our previous work, a multi-criteria spline algorithm prototype for a global path construction was developed and tested in Matlab environment. The algorithm used the Voronoi graph for computing an initial path that serves as a starting point of the iterative method. This approach allowed finding a path in all map configurations whenever the path existed. During the iterative search, a cost function with a number of different criteria and associated weights was guiding further path optimization. A potential field method was used to implement some of the criteria. This paper describes an implementation of a modified spline-based algorithm that could be used with real autonomous mobile robots. Equations of the characteristic criteria of a path optimality were further modified. The obstacle map was previously presented as intersections of a finite number of circles with various radii. However, in real world environments, obstacles’ data is a dynamically changing probability map that could be based on an occupancy grid. Moreover, the robot is no longer a geometric point. To implement the spline algorithm and further use it with real robots, the source code of the Matlab environment prototype was transferred into C++ programming language. The testing of the method and the multi criteria cost function optimality was carried out in ROS/Gazebo environment, which recently has become a standard for programming and modeling robotic devices and algorithms. The resulting spline-based path planning algorithm could be used on any real robot, which is equipped with a laser rangefinder. The algorithm operates in real time and the influence of the objective function criteria parameters are available for dynamic tuning during a robot motion.

Multi-level path planning algorithm for autonomous robots

1998 ◽  
Vol 34 (2) ◽  
pp. 223 ◽  
Author(s):  
C. Urdiales ◽  
A. Bandera ◽  
F. Arrebola ◽  
F. Sandoval
Keyword(s):  
Path Planning ◽  
Autonomous Robots ◽  
Planning Algorithm ◽  
Multi Level ◽  
Path Planning Algorithm

scholarly journals Intelligent Path Planning Approach for Autonomous Mobile Robot

2021 ◽  
Vol 33 (6) ◽  
pp. 1423-1428
Author(s):  
Ibrahim M. Al-Adwan ◽  
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Urban Environment ◽  
Optimal Path ◽  
Autonomous Mobile Robot ◽  
Current Position ◽  
Planning Approach ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Grid Based

This paper presents a new path planning algorithm for an autonomous mobile robot. It is desired that the robot reaches its goal in a known or partially known environment (e.g., a warehouse or an urban environment) and avoids collisions with walls and other obstacles. To this end, a new, efficient, simple, and flexible path finder strategy for the robot is proposed in this paper. With the proposed strategy, the optimal path from the robot’s current position to the goal position is guaranteed. The environment is represented as a grid-based map, which is then divided into a predefined number of subfields to reduce the number of required computations. This leads to a reduction in the load on the controller and allows a real-time response. To evaluate the flexibility and efficiency of the proposed strategy, several tests were simulated with environments of different sizes and obstacle distributions. The experimental results demonstrate the reliability and efficiency of the proposed algorithm.

Cosine Second Order Robot Trajectory Planning Method

2011 ◽  
Vol 80-81 ◽  
pp. 1075-1080
Author(s):  
Zong Wu Xie ◽  
Cao Li ◽  
Hong Liu
Keyword(s):  
Path Planning ◽  
Trajectory Planning ◽  
Trajectory Tracking ◽  
Joint Space ◽  
Planning Method ◽  
Robot Trajectory ◽  
Great Performance ◽  
Planning Methods ◽  
Planning Algorithm ◽  
Path Planning Algorithm

A new joint space trajectory planning method for the series robot is proposed. Comparing with the traditional path planning methods which can only guarantee the planned trajectory velocity or acceleration continuous, the proposed trajectory planning algorithm can also ensure the derivative of acceleration (Jerk) continuous within a limit threshold. At the end of this paper, the proposed path planning algorithm is validated of having a great performance on robot trajectory tracking.

The Research on Path Planning Algorithm of RoboCup Based on PFNPGA

2010 ◽  
Vol 20-23 ◽  
pp. 1192-1198
Author(s):  
Xian Yi Cheng ◽  
Qian Zhu ◽  
Zhen Wen Zhang
Keyword(s):  
Path Planning ◽  
Optimization Problem ◽  
Planning Process ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
The Poor ◽  
Starting Point ◽  
Planning Methods ◽  
Planning Algorithm ◽  
Path Planning Algorithm

To improve the poor efficiency in path planning that caused by not taking RoboCup’s stamina, character, dynamic starting point, dynamic endpoint and other factors into consideration in the path planning process, the RoboCup path planning is generalized as a multi-objective optimization problem in the paper, and proposes RoboCup’s sport model with dynamic multi-objective path planning which is based on RoboCup’s stamina triple model, and a path planning algorithm that is suited for RoboCup is advanced based on PFNPGA ( Penalty Function Niche Pareto Genetic Algorithm）. The experiment in a real environment shows that, by comparing with traditional path planning methods, the algorithm in the paper can get more reasonable path at the premise of guarantee RoboCup have relative high stamina values.

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