An Improved Chaotic Motion Path Planner for Autonomous Mobile Robots Based on a Logistic Map

Li, Caihong; Wang, Fengying; Zhao, Lei; Li, Yibin; Song, Yong

doi:10.5772/56587

Cited by 25 publications

(16 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Another method for this technique is to use the RPP (Random Path Planners) [11], [20], which avoids local minima by combining the concept of artificial potential areas with random search techniques. Similar method that can achieve significant results for such problems is the PRM (Probabilistic Roadmap Planners) planner [11], [21], which uses probability-based algorithms such as random sampling.…”

Section: Path Planning: Artifical Potential Techniquesmentioning

confidence: 99%

Path and Trajectory Planning for an Automated Carrier Vehicle Equipped with two Conveyor Belts used in Manufacturing Supply

Cservenák¹

2021

Manufacturing Technology

View full text Add to dashboard Cite

The AGVs or mobile robots are well used in today's manufacturing supply technologies and also can be used in engineering's education. The motion controlling and simulation of such vehicles are a crucial question. This paper introduces the steps of motion planning for a driverless carrier vehicle from the positions initially available to the speed of the wheels. The vehicle is located in the High-Tech Logistics Systems Laboratory of the Logistics Institute of the University of Miskolc. For motion controlling and simulation between two points the further modules are necessary: 1. path planner, 2. trajectory planner, 3. velocity-voltage converter using velocities gained from trajectory planner, 4. motion controlling and simulation of a motor dynamical model using voltages from the converter, 5. simulation of the path and 6. data processing. In this paper the first two modules are detailed, i.e. the path planning and then the trajectory planning. Path planning is based on a new approach, using Bezier-curves and Hermite curves. The trajectory planning tends to the mininum energy, which can be carried out by the examining the current consumption created in the other modules. The smaller consumption originated from the two curves determines the final path and trajectory.

show abstract

Section: Path Planning: Artifical Potential Techniquesmentioning

confidence: 99%

Path and Trajectory Planning for an Automated Carrier Vehicle Equipped with two Conveyor Belts used in Manufacturing Supply

Cservenák¹

2021

Manufacturing Technology

View full text Add to dashboard Cite

show abstract

“…Caihong et al suggested a chaotic path planner based on a logistic map. This simple deterministic system behaved randomly and traversed large workspace coverage [71]. They also presented a fusion strategy based on the Standard map for developing a chaotic path planner for mobile robots [72].…”

Section: Chaos Synthesis In Roboticsmentioning

confidence: 99%

Applications of Chaotic Dynamics in Robotics

Zang

Iqbal

Zhu

et al. 2016

International Journal of Advanced Robotic Systems

View full text Add to dashboard Cite

This article presents a summary of applications of chaos and fractals in robotics. Firstly, basic concepts of deterministic chaos and fractals are discussed. Then, fundamental tools of chaos theory used for identifying and quantifying chaotic dynamics will be shared. Principal applications of chaos and fractal structures in robotics research, such as chaotic mobile robots, chaotic behaviour exhibited by mobile robots interacting with the environment, chaotic optimization algorithms, chaotic dynamics in bipedal locomotion and fractal mechanisms in modular robots will be presented. A brief survey is reported and an analysis of the reviewed publications is also presented.

show abstract

“…Among these methods, generating factors (such as the random number in equation ( 6)) are most common and simplest way. 48 Typical discrete chaotic maps include logistic map, 49 tent map, 50 Chebyshev map, 51 and so on. Compared with logistic and tent maps with the distribution range from 0 to 1, Chebyshev map has a wider distribution, from À1 to 1.…”

Section: The Introduction Of Chaosmentioning

confidence: 99%

Hybrid chaos-based particle swarm optimization-ant colony optimization algorithm with asynchronous pheromone updating strategy for path planning of landfill inspection robots

Chen

Zhang³

et al. 2019

International Journal of Advanced Robotic Systems

View full text Add to dashboard Cite

Robots are coming to help us in different harsh environments such as deep sea or coal mine. Waste landfill is the place like these with casualty risk, gas poisoning, and explosion hazards. It is reasonable to use robots to fulfill tasks like burying operation, transportation, and inspection. In these assignments, one important issue is to obtain appropriate paths for robots especially in some complex applications. In this context, a novel hybrid swarm intelligence algorithm, ant colony optimization enhanced by chaos-based particle swarm optimization, is proposed in this article to deal with the path planning problem for landfill inspection robots in Asahikawa, Japan. In chaos-based particle swarm optimization, Chebyshev chaotic sequence is used to generate the random factors for particle swarm optimization updating formula so as to effectively adjust particle swarm optimization parameters. This improved model is applied to optimize and determine the hyper parameters for ant colony optimization. In addition, an improved pheromone updating strategy which combines the global asynchronous feature and “Elitist Strategy” is employed in ant colony optimization in order to use global information more appropriately. Therefore, the iteration number of ant colony optimization invoked by chaos-based particle swarm optimization can be reduced reasonably so as to decrease the search time effectively. Comparative simulation experiments show that the chaos-based particle swarm optimization-ant colony optimization has a rapid search speed and can obtain solutions with similar qualities.

show abstract

An Improved Chaotic Motion Path Planner for Autonomous Mobile Robots Based on a Logistic Map

Cited by 25 publications

References 13 publications

Path and Trajectory Planning for an Automated Carrier Vehicle Equipped with two Conveyor Belts used in Manufacturing Supply

Path and Trajectory Planning for an Automated Carrier Vehicle Equipped with two Conveyor Belts used in Manufacturing Supply

Applications of Chaotic Dynamics in Robotics

Hybrid chaos-based particle swarm optimization-ant colony optimization algorithm with asynchronous pheromone updating strategy for path planning of landfill inspection robots

Contact Info

Product

Resources

About