Hardware Schemes for Smarter Indoor Robotics to Prevent the Backing Crash Framework Using Field Programmable Gate Array-Based Multi-Robots

Author:

Basha Mudasar12ORCID,Siva Kumar Munuswamy1,Chinnaiah Mangali Chinna23ORCID,Lam Siew-Kei3,Srikanthan Thambipillai3,Narambhatla Janardhan4ORCID,Dodde Hari Krishna2ORCID,Dubey Sanjay2ORCID

Affiliation:

1. Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Green Fields, Guntur 522502, Andhra Pradesh, India

2. Department of Electronics and Communications Engineering, B. V. Raju Institute of Technology, Medak Dist., Narsapur 502313, Telangana, India

3. School of Computer Science and Engineering, Nanyang Technological University, Singapore 639798, Singapore

4. Department of Mechanical Engineering, Chaitanya Bharati Institute of Technology, Gandipet, Hyderabad 500075, Telangana, India

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.

Publisher

MDPI AG

Reference30 articles.

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4. Raja, V., Talwar, D., Manchikanti, A., and Jha, S. (2023). Industry 4.0 and Advanced Manufacturing, Springer.

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