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Optimization of Path Planning for Construction Robots Based on Multiple Advanced Algorithms  [PDF]
Kang Tan
Journal of Computer and Communications (JCC) , 2018, DOI: 10.4236/jcc.2018.67001
Abstract: There are many processes involved in construction, it is necessary to optimize the path planning of construction robots. Most researches focused more on optimization algorithms, but less on comparative analysis based on the advantages and shortcomings of these algorithms. Therefore, the innovation of this paper is to analyze three advanced optimization algorithms (genetic algorithm, hybrid particle swarm algorithm and ant colony algorithm) and discuss how these algorithms can improve the optimization performance by adjusting parameters. Finally, the three algorithms are compared and analyzed to find an optimization algorithm that is suitable for path planning optimization of construction robots. The purpose of the optimization is to obtain the maximum benefit with the least cost and complete project in an efficient and economical way.
Path Planning for Mobile Robots Based on Hybrid Architecture Platform  [cached]
Ting Zhou,Xiaoping Fan,Shengyue Yang,Zhihua Qu
Computer and Information Science , 2010, DOI: 10.5539/cis.v3n3p117
Abstract: In this paper, a hybrid architecture is used to develop the software platform of path planning of mobile robots. It consists of four levels: the decision-making layer, the behavior layer, the command parsing layer and the hardware communication layer. The whole framework of the decision-making system is based on the global planning, which is realized by using the ant colony algorithm. In the process of movement, the robot detects the real-time local information using the sensors mounted on it, and calls diffident behaviour objects to revise the global path for diffident situations. The experimental results show that the mobile robot has good capacity for unexpected situations in the process of moving along the optimal path.
Path Planning for Mobile Robots using Iterative Artificial Potential Field Method
Hossein Adeli,M H N Tabrizi,Alborz Mazloomian,Ehsan Hajipour
International Journal of Computer Science Issues , 2011,
Abstract: In this paper, a new algorithm is proposed for solving the path planning problem of mobile robots. The algorithm is based on Artificial Potential Field (APF) methods that have been widely used for path planning related problems for more than two decades. While keeping the simplicity of traditional APF methods, our algorithm is built upon new potential functions based on the distances from obstacles, destination point and start point. The algorithm uses the potential field values iteratively to find the optimum points in the workspace in order to form the path from start to destination. The number of iterations depends on the size and shape of the workspace. The performance of the proposed algorithm is tested by conducting simulation experiments.
Research on stereo vision pathplanning algorithms for mobile robots autonomous navigation
ZHANG Guowei,LU Qiuhong
重庆邮电大学学报(自然科学版) , 2009,
Abstract: Using stereo vision for autonomous mobile robot pathplanning is a hot technology. The environment mapping and pathplanning algorithms were introduced, and they were applied in the autonomous mobile robot experiment platform. Through experiments in the robot platform, the effectiveness of these algorithms was verified.
Path Planning and Trajectory Control of Collaborative Mobile Robots Using Hybrid Control Architecture
Trevor Davies,Amor Jnifene
Journal of Systemics, Cybernetics and Informatics , 2008,
Abstract: This paper presents the development and implementation a hybrid control architecture to direct a collective of three X80 mobile robots to multiple user-defined waypoints. The Genetic Algorithm Path Planner created an optimized, reduction in the time to complete the task, path plan for each robot in the collective such that each waypoint was visited once without colliding with a priori obstacles. The deliberative Genetic Algorithm Path Planner was then coupled with a reactive Potential Field Trajectory Planner and kinematic based controller to create a hybrid control architecture allowing the mobile robot to navigate between multiple user-defined waypoints, while avoiding a priori obstacles and obstacles detected using the robots' range sensors. The success of this hybrid control architecture was proven through simulation and experimentation using three of Dr. Robot's wireless X80 mobile robots.
CA Based Path Planning Method for Mobile Robots Enhanced by ant Colony Inspired Mechanis  [cached]
Adel Akbarimajd,Akbar Hassan Zadeh
Intelligent Systems in Electrical Engineering , 2011,
Abstract: In path planning of mobile robots dealing with concave obstacles is a major challenge. More specifically in real-time planning where there is no complete representation of the environment, this challenge would be much more problematic. In such cases local minimums and high computations cost are the most important problems. In this paper, in order to reduce computational cost, cellular automata as a distributed computational method with parallel processing properties is employed as tool for path planning purposes. The environment of the robot is modeled as a two dimensional cellular automata with four states. Evolutionary rules of the automata are proposed to perform the planning task. The proposed method is appropriate for single robot systems as well as multi robot systems. The proposed method is afterwards extended to be employed for concave obstacles using a ant colony inspired technique. The most superior advantage of the proposed method is its capability of real-time path planning of mobile robots with no need to prior representation of the environment.
Real-Time Collision-Free Path Planning for Robots in Configuration Space
Li Wei,Zhang Bo,
Li Wei
,Zhang Bo,Hilmar Jaschek

计算机科学技术学报 , 1994,
Abstract: Collision-free path planning for an industrtal robot in configuration space requires mapping obstacles from robot's workspace into its configuration space. In this paper ,an approach to real-time collision-free path planning for robots in configuration space is presented. Obstacle mapping is carried out by fundamental obstacles defined in the workspace and their images in the configuration space. In order to avoid dealing with unimportant parts of the configuration space that do not thect searching a collision-free path between starting and goal configurations, we construct a free subspace by slice configuration obstacles. In this free subspace, the collision-free path is determined by the A algorithm. Finally, graphical simulations show the effectiveness of the proposed approach.
A Path Planning Algorithm using Generalized Potential Model for Hyper- Redundant Robots with 2-DOF Joints
Chien-Chou Lin,Jen-Hui Chuang,Cheng-Tieng Hsieh
International Journal of Advanced Robotic Systems , 2011,
Abstract: This paper proposes a potential‐based path planning algorithm of articulated robots with 2‐DOF joints. The algorithm is an extension of a previous algorithm developed for 3‐DOF joints. While 3‐DOF joints result in a more straightforward potential minimization algorithm, 2‐DOF joints are obviously more practical for active operations. The proposed approach computes repulsive force and torque between charged objects by using generalized potential model. A collision‐free path can be obtained by locally adjusting the robot configuration to search for minimum potential configurations using these force and torque. The optimization of path safeness, through the innovative potential minimization algorithm, makes the proposed approach unique. In order to speedup the computation, a sequential planning strategy is adopted. Simulation results show that the proposed algorithm works well compared with 3‐DOF‐joint algorithm, in terms of collision avoidance and computation efficiency.
Research on the mobile robots intelligent path planning based on ant colony algorithm application in manufacturing logistics  [PDF]
Yue Guo,Xuelian Shen,Zhanfeng Zhu
Computer Science , 2014,
Abstract: With the development of robotics and artificial intelligence field unceasingly thorough, path planning as an important field of robot calculation has been widespread concern. This paper analyzes the current development of robot and path planning algorithm and focuses on the advantages and disadvantages of the traditional intelligent path planning as well as the path planning. The problem of mobile robot path planning is studied by using ant colony algorithm, and it also provides some solving methods.
Admissible Velocity Propagation : Beyond Quasi-Static Path Planning for High-Dimensional Robots  [PDF]
Quang-Cuong Pham,Stéphane Caron,Puttichai Lertkultanon,Yoshihiko Nakamura
Computer Science , 2014,
Abstract: Path-velocity decomposition is an intuitive yet powerful approach to address the complexity of kinodynamic motion planning. The difficult trajectory planning problem is solved in two separate, simpler, steps: first, find a path in the configuration space that satisfies the geometric constraints (path planning), and second, find a time-parameterization of that path satisfying the kinodynamic constraints. A fundamental requirement is that the path found in the first step should be time-parameterizable. Most existing works fulfill this requirement by enforcing quasi-static constraints in the path planning step, resulting in an important loss in completeness. We propose a method that enables path-velocity decomposition to discover truly dynamic motions, i.e. motions that are not quasi-statically executable. At the heart of the proposed method is a new algorithm -- Admissible Velocity Propagation -- which, given a path and an interval of reachable velocities at the beginning of that path, computes exactly and efficiently the interval of all the velocities the system can reach after traversing the path while respecting the system kinodynamic constraints. Combining this algorithm with usual sampling-based planners then gives rise to a family of new trajectory planners that can appropriately handle kinodynamic constraints while retaining the advantages associated with path-velocity decomposition. We demonstrate the efficiency of the proposed method on some difficult kinodynamic planning problems, where, in particular, quasi-static methods are guaranteed to fail.
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