Zobrazeno 1 - 10
of 1 263
pro vyhledávání: '"autonomous mobile robots"'
Publikováno v:
The International Journal of Logistics Management, 2023, Vol. 35, Issue 4, pp. 1168-1199.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IJLM-09-2022-0362
Autor:
Pui Yee Leong, Nur Syazreen Ahmad
Publikováno v:
IEEE Access, Vol 12, Pp 164248-164261 (2024)
Research on autonomous vehicles (AV) - self-navigating machines that transport both man and cargo has proliferated lately. While once limited to industrial or military uses, more attention is now given to their potential applications in broader socie
Externí odkaz:
https://doaj.org/article/ead81edddb094de59effa54439d5a898
Autor:
Pui Yee Leong, Nur Syazreen Ahmad
Publikováno v:
IEEE Access, Vol 12, Pp 131395-131417 (2024)
This review paper provides a detailed overview of the advancements and identifies pivotal challenges in the realm of autonomous load-carrying mobile robots, with a particular focus on indoor applications for both ground and aerial platforms. It criti
Externí odkaz:
https://doaj.org/article/da4ade0c6fdb4bc4802041acf385240b
Publikováno v:
IEEE Access, Vol 12, Pp 75366-75383 (2024)
Real-time locating systems (RTLSs) have proven to be a practical and effective solution for monitoring positions/status of humans and other entities in industrial environments, ensuring safe and efficient automated operations, by responding in real-t
Externí odkaz:
https://doaj.org/article/e8ac11234d274f4aa4e7f87acac80e90
Publikováno v:
IEEE Access, Vol 12, Pp 68711-68729 (2024)
This paper introduces the Kabsch Marker Estimation Algorithm (KMEA), a new, robust multi-marker localization method designed for Autonomous Mobile Robots (AMRs) within Industry 4.0 (I4.0) settings. By integrating the Kabsch Algorithm, our approach si
Externí odkaz:
https://doaj.org/article/efa38078f333421b984816a83e3568b4
Publikováno v:
Buildings, Vol 14, Iss 11, p 3615 (2024)
The increasing adoption of advanced technologies and the growing demand for automation have driven the development of innovative solutions for smart Facilities Management (FM). The COVID-19 pandemic accelerated this trend, highlighting the need for g
Externí odkaz:
https://doaj.org/article/2e0b87649ef942ba8ea0ecb5861e6dc0
Publikováno v:
Robotic Intelligence and Automation, 2023, Vol. 43, Issue 6, pp. 648-668.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/RIA-05-2023-0060
Trajectory tracking for non-holonomic mobile robots: A comparison of sliding mode control approaches
Publikováno v:
Results in Engineering, Vol 22, Iss , Pp 102105- (2024)
This paper implements and compares the performance of three controllers based on Sliding Mode Control (SMC) applied to the motion control of mobile robots. The controllers include a standard SMC controller and two variations, namely Dynamic Sliding M
Externí odkaz:
https://doaj.org/article/137376d3928d4c328d8fc1705f9b3b53
Autor:
Ákos Cservenák, Jozef Husár
Publikováno v:
Applied Sciences, Vol 14, Iss 17, p 7965 (2024)
This paper presents the development of a multidisciplinary learning model using automated guided vehicles (AGVs) and autonomous mobile robots (AMRs) for laboratory courses, focusing on Industry 4.0 and 5.0 paradigms. Industry 4.0 and 5.0 emphasize ad
Externí odkaz:
https://doaj.org/article/d97a534bea9d41a0b692396db3a992bf
Publikováno v:
Applied Sciences, Vol 14, Iss 17, p 7654 (2024)
Path planning is a fundamental task for autonomous mobile robots (AMRs). Classic approaches provide an analytical solution by searching for the trajectory with the shortest distance; however, reinforcement learning (RL) techniques have been proven to
Externí odkaz:
https://doaj.org/article/7b5455fe4d0f41c2b8fae15fc4e4619f