CELLULAR AUTOMATA AND OPTIMAL PATH PLANNING

1996 ◽  
Vol 06 (03) ◽  
pp. 603-610 ◽  
Author(s):  
M. STÄMPFLE
Keyword(s):  
Cellular Automata ◽  
Path Planning ◽  
Optimal Path ◽  
Shortest Paths ◽  
Optimal Solution ◽  
Starting Position ◽  
Optimal Path Planning ◽  
Time Space ◽  
Neural Network Theory ◽  
Optimal Configurations

Cellular automata are deterministic dynamical systems in which time, space, and state values are discrete. Although they consist of uniform elements, which interact only locally, cellular automata are capable of showing complex behavior. This property is exploited for solving path planning problems in workspaces with obstacles. A new automaton rule is presented which calculates simultaneously all shortest paths between a starting position and a target cell. Based on wave propagation, the algorithm ensures that the dynamics settles down in an equilibrium state which represents an optimal solution. Rule extensions include calculations with multiple starts and targets. The method allows applications on lattices and regular, weighted graphs of any finite dimension. In comparison with algorithms from graph theory or neural network theory, the cellular automaton approach has several advantages: Convergence towards optimal configurations is guaranteed, and the computing costs depend only linearly on the lattice size. Moreover, no floating-point calculations are involved.

scholarly journals AGV optimal path planning based on improved ant colony algorithm

2018 ◽  
Vol 232 ◽  
pp. 03052 ◽  
Author(s):  
Chengwei He ◽  
Jian Mao
Keyword(s):  
Path Planning ◽  
Ant Colony Algorithm ◽  
Optimal Path ◽  
Optimal Solution ◽  
Ant Colony ◽  
Undirected Network ◽  
Optimal Path Planning ◽  
Local Optimal Solution ◽  
Global Optimal ◽  
Improved Ant Colony Algorithm

Using the traditional Ant Colony Algorithm for AGV path planning is easy to fall into the local optimal solution and lacking the capability of obstacle avoidance in the complex storage environment. In this paper, by constructing the MAKLINK undirected network routes and the heuristic function is optimized in the Ant Colony Algorithm, then the AGV path reaches the global optimal path and has the ability to avoid obstacles. According to research, the improved Ant Colony Algorithm proposed in this paper is superior to the traditional Ant Colony Algorithm in terms of convergence speed and the distance of optimal path planning.

Optimal Path Planning for Painting Robots

2010 ◽  
Author(s):  
A. Gasparetto ◽  
R. Vidoni ◽  
E. Saccavini ◽  
D. Pillan
Keyword(s):  
Path Planning ◽  
Optimal Path ◽  
Optimal Solution ◽  
Minimum Length ◽  
Planning Problem ◽  
Optimal Path Planning ◽  
Chinese Postman ◽  
Velocity Motion ◽  
Learning Programming ◽  
Robotic Painting

In this work, a robotic painting task is addressed in order to automate and improve the efficiency of the process. Usually, path planning in robotic painting is done through self learning programming. Recently, different automated and semi-automated systems have been developed in order to avoid this procedure by using a CAD-drawing to create a CAD-guided trajectory for the paint gun, or by acquiring and recognizing the overall shape of the object to be painted within a library of prestored shapes with associated pre-defined paths. However, a general solution is still lacking, which enables one to overcome the need for a CAD-drawing and to deal with any kind of shapes. In this paper, graph theory and operative research techniques are applied to provide a general and optimal solution of the path planning problem for painting robots. The object to be painted is partitioned into primitives that can be represented by a graph. The Chinese Postman algorithm is then run on the graph in order to obtain a minimum length path covering all the arcs (Eulerian path). However, this path is not always optimal with respect to the constraints imposed by the painting process, hence dedicated algorithms have been developed in order to generate the optimal path in such cases. Based on the optimal path, the robot trajectories are planned by imposing a constant velocity motion of the spray gun, in order to ensure a uniform distribution of the paint over the object surface. The proposed system for optimal path planning has been implemented in a Matlab environment and extensively tested with excellent results in terms of time, costs and usability.

Method of evolving junctions: A new approach to optimal path-planning in 2D environments with moving obstacles

2017 ◽  
Vol 36 (4) ◽  
pp. 403-413 ◽  
Author(s):  
Wuchen Li ◽  
Shui-Nee Chow ◽  
Magnus Egerstedt ◽  
Jun Lu ◽  
Haomin Zho
Keyword(s):  
Path Planning ◽  
Optimal Path ◽  
Optimal Solution ◽  
Optimization Method ◽  
Planning Problem ◽  
Optimal Path Planning ◽  
Moving Obstacles ◽  
Finite Dimensional ◽  
General Convex ◽  
Global Optimal

We propose a novel algorithm to find the global optimal path in 2D environments with moving obstacles, where the optimality is understood relative to a general convex continuous running cost. By leveraging the geometric structures of optimal solutions and using gradient flows, we convert the path-planning problem into a system of finite dimensional ordinary differential equations, whose dimensions change dynamically. Then a stochastic differential equation based optimization method, called intermittent diffusion, is employed to obtain the global optimal solution. We demonstrate, via numerical examples, that the new algorithm can solve the problem efficiently.

scholarly journals Time-optimal Path Planning of Multi-axis CNC Processes Using Variability of Orientation

Procedia CIRP ◽  
2021 ◽  
Vol 96 ◽  
pp. 324-329
Author(s):  
Frederik Wulle ◽  
Max Richter ◽  
Christoph Hinze ◽  
Alexander Verl
Keyword(s):  
Path Planning ◽  
Optimal Path ◽  
Optimal Path Planning ◽  
Time Optimal

scholarly journals A CNN-based scheme for COVID-19 detection with emergency services provisions using an optimal path planning

2021 ◽  
Author(s):  
Ahmed Barnawi ◽  
Prateek Chhikara ◽  
Rajkumar Tekchandani ◽  
Neeraj Kumar ◽  
Mehrez Boulares
Keyword(s):  
Path Planning ◽  
Emergency Services ◽  
Optimal Path ◽  
Optimal Path Planning

scholarly journals COLREG-Compliant Optimal Path Planning for Real-Time Guidance and Control of Autonomous Ships

2021 ◽  
Vol 9 (4) ◽  
pp. 405
Author(s):  
Raphael Zaccone
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Collision Avoidance ◽  
Autonomous Navigation ◽  
Optimal Path ◽  
Open Water ◽  
Optimal Path Planning ◽  
Guidance And Control ◽  
Real Time Applications ◽  
And Control

While collisions and groundings still represent the most important source of accidents involving ships, autonomous vessels are a central topic in current research. When dealing with autonomous ships, collision avoidance and compliance with COLREG regulations are major vital points. However, most state-of-the-art literature focuses on offline path optimisation while neglecting many crucial aspects of dealing with real-time applications on vessels. In the framework of the proposed motion-planning, navigation and control architecture, this paper mainly focused on optimal path planning for marine vessels in the perspective of real-time applications. An RRT*-based optimal path-planning algorithm was proposed, and collision avoidance, compliance with COLREG regulations, path feasibility and optimality were discussed in detail. The proposed approach was then implemented and integrated with a guidance and control system. Tests on a high-fidelity simulation platform were carried out to assess the potential benefits brought to autonomous navigation. The tests featured real-time simulation, restricted and open-water navigation and dynamic scenarios with both moving and fixed obstacles.

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