Hybrid rule-based motion planner for mobile robot in cluttered
workspace

J 2018

Hybrid rule-based motion planner for mobile robot in cluttered workspace

ABBADI, Ahmad and Radomil MATOUSEK

Basic information

Original name

Hybrid rule-based motion planner for mobile robot in cluttered workspace

Authors

ABBADI, Ahmad (760 Syrian Arab Republic, belonging to the institution) and Radomil MATOUSEK (203 Czech Republic)

Edition

Soft computing, Germany, Springer, 2018, 1432-7643

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

20200 2.2 Electrical engineering, Electronic engineering, Information engineering

Country of publisher

Germany

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

URL

Impact factor

Impact factor: 2.784

RIV identification code

RIV/00216224:14330/18:00101937

Organization unit

Faculty of Informatics

DOI

http://dx.doi.org/10.1007/s00500-016-2103-4

UT WoS

000426761200008

Keywords in English

Motion planning; Path planning; Rule-based; Sampling-based planner; Guided planner; RRT; Cell decomposition; Adaptive sampling

Abstract

V originále

Motion planning problem is an active field in robotics. It is concerned with converting high-level task specifications into low-level descriptions of how to move and provides a feasible sequence of movements that avoid obstacles while respecting kinematic and dynamic equations. In this work, new planners are designed with the aim of developing an efficient motion planner in a heterogeneous, cluttered, and dynamic workspace. The planners are composed of two layers, and they use a rule-based system as a guidance. The first layer uses exact cell decomposition method, which divides the workspace into manageable regions and finds the adjacency information for them. The second layer utilizes rapidly exploring random tree algorithm RRT that finds a solution in a cluttered workspace. The adjacency information of the free cells and the exploration information that is provided by RRT are combined and utilized to help the planners classifying the free regions and guiding the growth of RRT trees efficiently toward the most important areas. Two types of the planners are proposed, the first one uses adviser that pulls the trees' growth toward the boundary areas between explored and unexplored regions, while the adviser of the second planner uses the collision information and fuzzy rules to guide the trees' growth toward areas that have low collision rate around the boundaries of explored regions. The planners are tested in stationary as well as in changed workspace. The proposed methods have been compared to other approaches and the simulation results show that they yield better results in terms of completeness and efficiency.

Citovat

ABBADI, Ahmad and Radomil MATOUSEK. Hybrid rule-based motion planner for mobile robot in cluttered workspace. Soft computing. Germany: Springer, 2018, vol. 22, No 6, p. 1815-1831. ISSN 1432-7643. Available from: https://dx.doi.org/10.1007/s00500-016-2103-4.

@article{1339218,
   author = {Abbadi, Ahmad and Matousek, Radomil},
   article_location = {Germany},
   article_number = {6},
   doi = {http://dx.doi.org/10.1007/s00500-016-2103-4},
   keywords = {Motion planning; Path planning; Rule-based; Sampling-based planner; Guided planner; RRT; Cell decomposition; Adaptive sampling},
   language = {eng},
   issn = {1432-7643},
   journal = {Soft computing},
   title = {Hybrid rule-based motion planner for mobile robot in cluttered workspace},
   url = {http://dx.doi.org/10.1007/s00500-016-2103-4},
   volume = {22},
   year = {2018}
}

TY  - JOUR
ID  - 1339218
AU  - Abbadi, Ahmad - Matousek, Radomil
PY  - 2018
TI  - Hybrid rule-based motion planner for mobile robot in cluttered workspace
JF  - Soft computing
VL  - 22
IS  - 6
SP  - 1815-1831
EP  - 1815-1831
PB  - Springer
SN  - 14327643
KW  - Motion planning
KW  - Path planning
KW  - Rule-based
KW  - Sampling-based planner
KW  - Guided planner
KW  - RRT
KW  - Cell decomposition
KW  - Adaptive sampling
UR  - http://dx.doi.org/10.1007/s00500-016-2103-4
N2  - Motion planning problem is an active field in robotics. It is concerned with converting high-level task specifications into low-level descriptions of how to move and provides a feasible sequence of movements that avoid obstacles while respecting kinematic and dynamic equations. In this work, new planners are designed with the aim of developing an efficient motion planner in a heterogeneous, cluttered, and dynamic workspace. The planners are composed of two layers, and they use a rule-based system as a guidance. The first layer uses exact cell decomposition method, which divides the workspace into manageable regions and finds the adjacency information for them. The second layer utilizes rapidly exploring random tree algorithm RRT that finds a solution in a cluttered workspace. The adjacency information of the free cells and the exploration information that is provided by RRT are combined and utilized to help the planners classifying the free regions and guiding the growth of RRT trees efficiently toward the most important areas. Two types of the planners are proposed, the first one uses adviser that pulls the trees' growth toward the boundary areas between explored and unexplored regions, while the adviser of the second planner uses the collision information and fuzzy rules to guide the trees' growth toward areas that have low collision rate around the boundaries of explored regions. The planners are tested in stationary as well as in changed workspace. The proposed methods have been compared to other approaches and the simulation results show that they yield better results in terms of completeness and efficiency.
ER  -

ABBADI, Ahmad and Radomil MATOUSEK. Hybrid rule-based motion planner for mobile robot in cluttered workspace. \textit{Soft computing}. Germany: Springer, 2018, vol.~22, No~6, p.~1815-1831. ISSN~1432-7643. Available from: https://dx.doi.org/10.1007/s00500-016-2103-4.

Detailed Information on Publication Record