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https://hdl.handle.net/10356/178522
Title: | Hardware schemes for smarter indoor robotics to prevent the backing crash framework using field programmable gate array-based multi-robots | Authors: | Basha, Mudasar Siva Kumar, Munuswamy Chinnaiah, Mangali Chinna Lam, Siew-Kei Srikanthan, Thambipillai Narambhatla, Janardhan Dodde, Hari Krishna Dubey, Sanjay |
Keywords: | Computer and Information Science | Issue Date: | 2024 | Source: | Basha, M., Siva Kumar, M., Chinnaiah, M. C., Lam, S., Srikanthan, T., Narambhatla, J., Dodde, H. K. & Dubey, S. (2024). Hardware schemes for smarter indoor robotics to prevent the backing crash framework using field programmable gate array-based multi-robots. Sensors, 24(6), 1724-. https://dx.doi.org/10.3390/s24061724 | Journal: | Sensors | Abstract: | The use of smart indoor robotics services is gradually increasing in real-time scenarios. This paper presents a versatile approach to multi-robot backing crash prevention in indoor environments, using hardware schemes to achieve greater competence. Here, sensor fusion was initially used to analyze the state of multi-robots and their orientation within a static or dynamic scenario. The proposed novel hardware scheme-based framework integrates both static and dynamic scenarios for the execution of backing crash prevention. A round-robin (RR) scheduling algorithm was composed for the static scenario. Dynamic backing crash prevention was deployed by embedding a first come, first served (FCFS) scheduling algorithm. The behavioral control mechanism of the distributed multi-robots was integrated with FCFS and adaptive cruise control (ACC) scheduling algorithms. The integration of multiple algorithms is a challenging task for smarter indoor robotics, and the Xilinx-based partial reconfiguration method was deployed to avoid computational issues with multiple algorithms during the run-time. These methods were coded with Verilog HDL and validated using an FPGA (Zynq)-based multi-robot system. | URI: | https://hdl.handle.net/10356/178522 | ISSN: | 1424-8220 | DOI: | 10.3390/s24061724 | Schools: | College of Computing and Data Science School of Computer Science and Engineering |
Rights: | © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | CCDS Journal Articles |
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sensors-24-01724 (1).pdf | 7.44 MB | Adobe PDF | View/Open |
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