Wyniki wyszukiwania - Biblioteka Nauki

1

Chaotic path planning for grid coverage using a modified logistic-may map

100%

Petavratzis E. , Moysis L. , Volos C. , Nistazakis H. , Muñoz-Pacheco J. M. , Stouboulos I.

Journal of Automation Mobile Robotics and Intelligent Systems

|

2020

|

tom Vol. 14, No. 2

3--9

EN

A simple and efficient method for creating a motion trajectory is presented with an aim to achieve sufficient coverage of a given terrain. A chaotic map has been used in order that the motion trajectory should be unpredictable. The chaotic path generator which has been created, is used for implementing a robot’s movement in four and eight directions. The path generator is tested in various scenarios and the results are discussed. After thorough examination, the proposed method shows that the motion in eight directions gives better and very satisfactory results.

2

Using Diagnostic Information for Planning an Energy-Optimal Path of an Autonomous Vehicle

100%

Szulim P.

Logistics and Transport

|

2014

|

tom Vol. 21, No. 1

105--114

EN

The article has presented a general idea for an algorithm that would allow for determining the optimal parameters of vehicle movement. The sources of energy dissipation have been assumed as follows: damage to the engine and the drive. In addition, the mathematical basis have been presented for assessing the impact of damage resulting from problems such as axial misalignment on the dissipated energy. In the second part of the paper, the concept of the algorithm has been detailed, paying special attention to certain problems that have arisen, and an algorithm has been proposed that determines the optimal movement parameters for a simplified case, when the vehicle is moving along a path determined in advance. In addition, the results of applying the algorithm for a simple case have been presented, as well as the impact of the particular energy dissipation parameters of the model on the optimal velocity profile of the vehicle. The plans for further research include estimating the impact of other damages, such as damaged bearings or demagnetising, on the energy dissipation. Further work on an algorithm is also planned that would allow for simultaneous determining of an optimal path as well as an optimal velocity profile.

3

Some insights in path planning of small autonomous blimps

100%

Bestaoui Y. , Hima S.

Archives of Control Sciences

|

2001

|

tom Vol. 11, no. 3/4

139-166

EN

A blimp is a small airship that has no metal framework and collapses when deflated. In the first part of this paper, kinematics and dynamics modelling of small autonomous non rigid airships is presented. Euler angles and parameters are used in the formulation of this model. In the second part of the paper, path planning is introduced using helices with vertical axes. Motion generation for trim trajectories (helices with constant curvature and torsion) is presented. Then path planning using helices with quadratic curvature and torsion is described, and motion generation on these helices expressed. This motion generation takes into account the dynamics model presented.

4

Humanoid robot path planning using rapidly explored random tree and motion primitives

100%

Szumowski M. , Zielinska T.

Journal of Automation Mobile Robotics and Intelligent Systems

|

2021

|

tom Vol. 15, No. 1

24--30

EN

Path planning is an essential function of the control sy‐ stem of any mobile robot. In this article the path planner for a humanoid robot is presented. The short description of an universal control framework and the Motion Ge‐ neration System is also presented. Described path plan‐ ner utilizes a limited number of motions called the Mo‐ tion Primitives. They are generated by Motion Generation System. Four different algorithms, namely the: Informed RRT, Informed RRT with random bias, and RRT with A* like heuristics were tested. For the last one the version with biased random function was also considered. All menti‐ oned algorithms were evaluated considering three diffe‐ rent scenarios. Obtained results are described and discus‐ sed.

5

Ants Colony Optimisation of a Measuring Path of Prismatic Parts on a CMM

100%

Stojadinovic S. M. , Majstorovic V. D. , Durakbasa N. M. , Sibalija T. V.

Metrology and Measurement Systems

|

2016

|

tom Vol. 23, nr 1

119--132

EN

This paper presents optimisation of a measuring probe path in inspecting the prismatic parts on a CMM. The optimisation model is based on: (i) the mathematical model that establishes an initial collision-free path presented by a set of points, and (ii) the solution of Travelling Salesman Problem (TSP) obtained with Ant Colony Optimisation (ACO). In order to solve TSP, an ACO algorithm that aims to find the shortest path of ant colony movement (i.e. the optimised path) is applied. Then, the optimised path is compared with the measuring path obtained with online programming on CMM ZEISS UMM500 and with the measuring path obtained in the CMM inspection module of Pro/ENGINEER® software. The results of comparing the optimised path with the other two generated paths show that the optimised path is at least 20% shorter than the path obtained by on-line programming on CMM ZEISS UMM500, and at least 10% shorter than the path obtained by using the CMM module in Pro/ENGINEER®.

6

A collision avoidance algorithm in Simultaneous Localization and Mapping problem for mobile platforms

100%

Małecki T. , Narkiewicz J.

Journal of Theoretical and Applied Mechanics

|

2022

|

tom Vol. 60 nr 2

317--328

EN

A collision avoidance algorithm applicable in simultaneous localization and mapping (SLAM) has been developed with a prospect of an on-line application for mobile platforms to search and map the operation area and avoid contact with obstacles. The algorithm, which was implemented in MATLAB software, is based on a linear discrete-time state transition model for determination of the platform position and orientation, and a ‘force’ points method for collision avoidance and definition of the next-step of platform motion. The proposed approach may be incorporated into real-time applications with limited on-board computational resources.

7

Optimization-based approach to path planning for closed chain robot systems

100%

Szynkiewicz W. , Błaszczyk J.

International Journal of Applied Mathematics and Computer Science

|

2011

|

tom 21

|

nr 4

659-670

EN

An application of advanced optimization techniques to solve the path planning problem for closed chain robot systems is proposed. The approach to path planning is formulated as a “quasi-dynamic” NonLinear Programming (NLP) problem with equality and inequality constraints in terms of the joint variables. The essence of the method is to find joint paths which satisfy the given constraints and minimize the proposed performance index. For numerical solution of the NLP problem, the IPOPT solver is used, which implements a nonlinear primal-dual interior-point method, one of the leading techniques for large-scale nonlinear optimization.

8

Obstacle Avoidance Procedure and Lee Algorithm Based Path Replanner for Autonomous Mobile Platforms

100%

Polańczyk M. , Strzelecki M. , Ślot K.

International Journal of Electronics and Telecommunications

|

2013

|

tom Vol. 59, No. 1

85-91

EN

The paper proposes solution for two important issues connected to navigation of independent mobile platforms in an unknown environment. First issue relates to obstacle map, estimated based on stereovision images. It provides a basis for further platform path-planning. The main problem that has to be solved in obstacle map derivation is elimination of artifacts resulting from depth estimation. Thus a two-step artifact filtering procedure is proposed, which exploits both within-frame spatial correlations as well as temporal, between-frame correlations to do this task. Second procedure, based on well-known Lees algorithm is designed for obtaining vehicle collisionless path. Such routes need to be updated on-the-fly to take into account moving obstacles or newly detected objects. The main idea of the proposed approach is to identify regions where environment has changed and to execute a procedure of selective path updates. As a result, an optimal path can be derived at a computational expense comparable to the heuristic Lifelong A* search. Experiment results demonstrate efficiency of the two discussed approaches for platform operation control in real environments, where both static and moving obstacles are present.

9

Using Diagnostic Information for Planning an Energy-Optimal Path of an Autonomous Vehicle

100%

Szulim P.

Logistics and Transport

|

2014

|

tom 21

104-114

EN

The article has presented a general idea for an algorithm that would allow for determining the optimal parameters of vehicle movement. The sources of energy dissipation have been assumed as follows: damage to the engine and the drive. In addition, the mathematical basis have been presented for assessing the impact of damage resulting from problems such as axial misalignment on the dissipated energy. In the second part of the paper, the concept of the algorithm has been detailed, paying special attention to certain problems that have arisen, and an algorithm has been proposed that determines the optimal movement parameters for a simplified case, when the vehicle is moving along a path determined in advance. In addition, the results of applying the algorithm for a simple case have been presented, as well as the impact of the particular energy dissipation parameters of the model on the optimal velocity profile of the vehicle. The plans for further research include estimating the impact of other damages, such as damaged bearings or demagnetising, on the energy dissipation. Further work on an algorithm is also planned that would allow for simultaneous determining of an optimal path as well as an optimal velocity profile.

10

Planowanie trajektorii ruchu pojazdów sterowanych automatycznie

100%

Ulatowski W.

Pomiary Automatyka Robotyka

|

2003

|

tom R. 7, nr 12

16-19

PL

Przedstawiono metody planowania trajektorii ruchu autonomicznych pojazdów sterowanych automatycznie śledzących znaczniki umieszczone na powierzchni ruchu. Opisano najczęściej stosowane w robotyce metody planowania ścieżki oraz omówiono wady i zalety metod grafowych. Przedstawiono oraz dokonano weryfikacji metod „po omacku” oraz metod heurystycznych jako najczęściej wykorzystywanych grafowych metod planowania ścieżki. Zamieszczono przykłady obliczeniowe.

EN

The methods of path planning for AGVs which are tracking markers on the motion area are presented. This paper describes the most popular methods for path planning as well as faults and advantages of graphs methods. Depth-first search, breadth-first search and heuristic search as the most often used path planning methods are presented and verified. There are plenty of mathematical examples in this paper.

11

Reliable robust path planning with application to mobile robots

100%

Pepy R. , Kieffer M. , Walter E.

International Journal of Applied Mathematics and Computer Science

|

2009

|

tom 19

|

nr 3

413-424

EN

This paper is devoted to path planning when the safety of the system considered has to be guaranteed in the presence of bounded uncertainty affecting its model. A new path planner addresses this problem by combining Rapidly-exploring Random Trees (RRT) and a set representation of uncertain states. An idealized algorithm is presented first, before a description of one of its possible implementations, where compact sets are wrapped into boxes. The resulting path planner is then used for nonholonomic path planning in robotics.

12

Real-time coordinated trajectory planning and obstacle avoidance for mobile robots

100%

McNinch L. C. , Soltan R. A. , Muske K. R. , Ashrafiuon H. , Peyton J. C.

Journal of Automation Mobile Robotics and Intelligent Systems

|

2011

|

tom Vol. 5, No. 1

23-29

EN

A novel method for real-time coordinated trajectory planning and obstacle avoidance of autonomous mobile robot systems is presented. The desired autonomous system trajectories are generated from a set of first order ODEs. The solution to this system of ODEs converges to either a desired target position or a closed orbit de.ned by a limit cycle. Coordinated control is achieved by utilizing the nature of limit cycles where independent, non-crossing paths are automatically generated from different initial positions that smoothly converge to the desired closed orbits. Real-time obstacle avoidance is achieved by specifying a transitional elliptically shaped closed orbit around the nearest obstacle blocking the path. This orbit determines an alternate trajectory that avoids the obstacle. When the obstacle no longer blocks a direct path to the original target trajectory, a transitional trajectory that returns to the original path is defined. The coordination and obstacle avoidance methods are demonstrated experimentally using differential-drive wheeled mobile robots.

13

Collision-free autonomous robot navigation in unknown environments utilizing PSO for path planning

100%

Krell E. , Sheta A. , Balasubramanian A. P. R. , King S. A.

Journal of Artificial Intelligence and Soft Computing Research

|

2019

|

tom Vol. 9, No. 4

267--282

EN

The autonomous navigation of robots in unknown environments is a challenge since it needs the integration of a several subsystems to implement different functionality. It needs drawing a map of the environment, robot map localization, motion planning or path following, implementing the path in real-world, and many others; all have to be implemented simultaneously. Thus, the development of autonomous robot navigation (ARN) problem is essential for the growth of the robotics field of research. In this paper, we present a simulation of a swarm intelligence method is known as Particle Swarm Optimization (PSO) to develop an ARN system that can navigate in an unknown environment, reaching a pre-defined goal and become collision-free. The proposed system is built such that each subsystem manipulates a specific task which integrated to achieve the robot mission. PSO is used to optimize the robot path by providing several waypoints that minimize the robot traveling distance. The Gazebo simulator was used to test the response of the system under various envirvector representing a solution to the optimization problem.onmental conditions. The proposed ARN system maintained robust navigation and avoided the obstacles in different unknown environments. vector representing a solution to the optimization problem.

14

An optimal path planning problem for heterogeneous multi-vehicle systems

100%

Klaučo M. , Blažek S. , Kvasnica M.

International Journal of Applied Mathematics and Computer Science

|

2016

|

tom 26

|

nr 2

297-308

EN

A path planning problem for a heterogeneous vehicle is considered. Such a vehicle consists of two parts which have the ability to move individually, but one of them has a shorter range and is therefore required to keep in a close distance to the main vehicle. The objective is to devise an optimal path of minimal length under the condition that at least one part of the heterogeneous system visits all desired waypoints exactly once. Two versions of the problem are considered. One assumes that the order in which the waypoints are visited is known a priori. In such a case we show that the optimal path can be found by solving a mixed-integer second-order cone problem. The second version assumes that the order in which the waypoints are visited is not known a priori, but can be optimized so as to shorten the length of the path. Two approaches to solve this problem are presented and evaluated with respect to computational complexity.

15

Distributed Evolutionary Algorithm for Path Planning in Navigation Situation

100%

Śmierzchalski R. , Kuczkowski Ł. , Kolendo P. , Jaworski B.

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

|

2013

|

tom Vol. 7, no. 2

293--300

EN

This article presents the use of a multi‐population distributed evolutionary algorithm for path planning in navigation situation. The algorithm used is with partially exchanged population and migration between independently evolving populations. In this paper a comparison between a multi‐population and a classic single‐population algorithm takes place. The impact on the ultimate solution has been researched. It was shown that using several independent populations leads to an improvement of the ultimate solution compared to a single population approach. The concept was checked against a problem of maritime collision avoidance.

16

FDA* : a focused single‐query grid based path planning algorithm

100%

Boumediene M. , Lamine Mehennaoui L. , Lachouri A.

Journal of Automation Mobile Robotics and Intelligent Systems

|

2021

|

tom Vol. 15, No. 3

37--43

EN

Square grid representations of the state‐space are a commonly used tool in path planning. With applications in a variety of disciplines, including robotics, computational biology, game development, and beyond. However, in large‐scale and/or high dimensional environments the creation and manipulation of such structures become too expensive, especially in applications when an accurate representation is needed. In this paper, we present a method for reducing the cost of single‐query grid‐based path planning, by focusing the search to a smaller subset, that contains the optimal solution. This subset is represented by a hyperrectangle, the location, and dimensions of which are calculated departing from an initial feasible path found by a fast search using the RRT* algorithm. We also present an implementation of this focused discretization method called FDA*, a resolution optimal algorithm, where the A* algorithm is employed in searching the resulting graph for an optimal solution. We also demonstrate through simulation results, that the FDA* algorithm uses less memory and has a shorter run‐time compared to the classic A* and thus other graph‐based planning algorithms, and at the same time, the resulting path cost is less than that of regular RRT based algorithms.

17

Artifical potential fields with extended Bug algorithm for Mars rover path planning in an unknown environment

88%

Wyrąbkiewicz K. , Tarczewski T. , Grzesiak L. M.

Computer Applications in Electrical Engineering

|

2014

|

tom Vol. 12

422--433

EN

In this paper artificial potential fields method applied to autonomous mobile robot -mars rover is presented. It is assumed that Mars rover operates in an unknown environment. In order to visualize the robot's path in environment Matlab software is used. The object can be inserted by graphic data input interface in top view mode. The method of artificial potential fields is extended by an additional algorithm to avoid a local minimum. The proposed algorithm is implemented as a state machine. In this paper simulations results of the developed algorithm are presented. Extended algorithm is used because in the environment may be located complex obstacles.

18

Intelligent Control for a Perturbed Autonomous Wheeled Mobile Robot Using Type-2 Fuzzy Logic and Genetic Algorithms

88%

Martínez R. , Castillo O. , Aguilar L. T.

Journal of Automation Mobile Robotics and Intelligent Systems

|

2008

|

tom Vol. 2, No. 1

12-22

EN

We describe a tracking controller for the dynamic model of a unicycle mobile robot by integrating a kinematic and a torque controller based on Type-2 Fuzzy Logic Theory and Genetic Algorithms. Computer simulations are presented confirming the performance of the tracking controller and its application to different navigation problems.

19

Collision free path planning and control of wheeled mobile robot using Kohonen self-organising map

88%

Hendzel Z.

Bulletin of the Polish Academy of Sciences. Technical Sciences

|

2005

|

tom Vol. 53, nr 1

39-47

EN

In this paper we propose a sensor-based navigation method for navigation of wheeled mobile robot, based on the Kohonen self-organising map (SOM). We discuss a sensor-based approach to path design and control of wheeled mobile robot in an unknown 2-D environment with static obstacles. A strategy of reactive navigation is developed including two main behaviours: a reaching the middle of a collision-free space behaviour, and a goal-seeking behaviour. Each low-level behaviour has been designed at design stage and then fused to determine a proper actions acting on the environment at running stage. The combiner can fuse low-level behaviours so that the mobile robot can go for the goal position without colliding with obstacles one for the convex obstacles and one for the concave ones. The combiner is a softswitch, based on the idea of artificial potential fields, that chooses more then one action to be active with different degrees at each time step. The output of the navigation level is fed into a neural tracking controller that takes into account the dynamics of the mobile robot. The purpose of the neural controller is to generate the commands for the servo-systems of the robot so it may choose its way to its goal autonomously, while reacting in real-time to unexpected events. Computer simulation has been conducted to illustrate the performance of the proposed solution by a series of experiments on the emulator of wheeled mobile robot Pioneer-2DX.

20

Artifical potential fields algorithm for Mars rover path planning in an unknown enviroment

88%

Wyrąbkiewicz K. , Tarczewski T. , Grzesiak L. M.

Poznan University of Technology Academic Journals. Electrical Engineering

|

2014

|

tom No. 80

183--189

EN

In this paper artificial potential fields method applied to autonomous mobile robot - Mars rover is presented. It is assumed that Mars rover operates in an unknown environment. In order to visualize the robot's path in environment Matlab software is used. Inserted by graphic data input interface in top view mode obstacles are deployed in environment area. The method of artificial potential fields is extended by an additional algorithm to avoid a local minimum. The proposed algorithm is implemented as a state machine. In this paper simulations results of the developed algorithm are presented.