Pregled bibliografske jedinice broj: 1055070
Path planning optimization of six-degree-of- freedom robotic manipulators using evolutionary algorithms
Path planning optimization of six-degree-of- freedom robotic manipulators using evolutionary algorithms // International journal of advanced robotic systems, 17 (2020), 2; 1-16 doi:10.1177/1729881420908076 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 1055070 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Path planning optimization of six-degree-of-
freedom
robotic manipulators using evolutionary
algorithms
(Path planning optimization of six-degree-of-
freedom robotic
manipulators using evolutionary algorithms)
Autori
Baressi Šegota, Sandi ; Anđelić, Nikola ; Lorencin, Ivan ; Saga, Milan ; Car, Zlatan
Izvornik
International journal of advanced robotic systems (1729-8806) 17
(2020), 2;
1-16
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Artificial intelligence, cooperating robotic manipulators, differential evolution, genetic algorithm, robot trajectory planning, simulated annealing
Sažetak
Lowering joint torques of a robotic manipulator enables lowering the energy it uses as well as an increase in the longevity of the robotic manipulator. This article proposes the use of evolutionary computation algorithms for optimizing the paths of the robotic manipulator with the goal of lowering the joint torques. The robotic manipulator used for optimization is modeled after a realistic six-degree-of- freedom robotic manipulator. Two cases are observed and these are a single robotic manipulator carrying weight in a point-to-point trajectory and two robotic manipulators cooperating and moving the same weight along a calculated point-to-point trajectory. The article describes the process used for determining the kinematic properties using Denavit–Hartenberg method and the dynamic equations of the robotic manipulator using Lagrange–Euler and Newton–Euler algorithms. Then, the description of used artificial intelligence optimization algorithms is given – genetic algorithm using random and average recombination, simulated annealing using linear and geometric cooling strategy and differential evolution. The methods are compared and the results show that the genetic algorithm provides best results in regard to torque minimization, with differential evolution also providing comparatively good results and simulated annealing giving the comparatively weakest results while providing smoother torque curves.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Računarstvo, Strojarstvo, Temeljne tehničke znanosti
POVEZANOST RADA
Projekti:
Ostalo-CEI - 305.6019-20 - Use of regressive artificial intelligence (AI) and machine learning (ML) methods in modelling of COVID-19 spread (COVIDAi) (Car, Zlatan, Ostalo - CEI Extraordinary Call for Proposals 2020) ( CroRIS)
--KK.01.2.2.03.0004 - Centar kompetencija za pametne gradove (CEKOM) (Car, Zlatan; Slavić, Nataša; Vilke, Siniša) ( CroRIS)
NadSve-Sveučilište u Rijeci-uniri-tehnic-18-275-1447 - Razvoj inteligentnog ekspertnog sustava za online diagnostiku raka mokračnog mjehura (Car, Zlatan, NadSve - UNIRI potpore) ( CroRIS)
InoUstZnVO-CIII-HR-0108-10 - Concurrent Product and Technology Development - Teaching, Research and Implementation of Joint Programs Oriented in Production and Industrial Engineering (Car, Zlatan, InoUstZnVO - CEEPUS) ( CroRIS)
--KK.01.1.1.01.009 - Napredne metode i tehnologije u znanosti o podatcima i kooperativnim sustavima (DATACROSS) (Šmuc, Tomislav; Lončarić, Sven; Petrović, Ivan; Jokić, Andrej; Palunko, Ivana) ( CroRIS)
uniri-tehnic-18-275-1447
CEEPUS CIII-HR-0108
DATACROSS KK.01.1.1.01.0009
VEGA 1/0504/17
Ustanove:
Tehnički fakultet, Rijeka
Profili:
Zlatan Car
(autor)
Nikola Anđelić
(autor)
Sandi Baressi Šegota
(autor)
Ivan Lorencin
(autor)
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus