Open AccessPower-efficient Strategies for Sensing in Autonomous Mobile Robots, a critical requirement of I4.0 standard
Author(s) -
Jyoti Bali,
H Arpitha,
N Anushree,
Arunkumar C. Giriyapur
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1187/1/012007
Subject(s) - field programmable gate array , efficient energy use , computer science , robot , embedded system , sensor fusion , energy consumption , focus (optics) , mobile robot , controller (irrigation) , fuse (electrical) , control engineering , real time computing , engineering , artificial intelligence , electrical engineering , agronomy , physics , optics , biology
In a production environment, there are several challenges in meeting the Industry 4.0 (I4.0) standard requirements. Energy efficiency is an essential area of focus. In the production setup, the critical and real-time control systems need to be very efficient while implementing functions, namely, accurate sensing, fast processing and precise actuation. Automated Guided vehicles (AGVs) and Automated Guided Vehicles are an integral part of modern and intelligent manufacturing systems. Power consumption in such systems is directly proportional to the performance level achieved. However, there is a need to evolve strategies to reduce power consumption and attain optimal performance. Field Programmable Gate Array(FPGA) based controller solutions can provide competent performance at optimized power consumption. The proposed work discusses the requirements of I4.0 concerning energy efficiency infrastructures for the intelligent manufacturing setup. The need to develop efficient subsystems for sensing, decision-making and actuation based on FPGA is stressed. Thus the focus is on the FPGA based power-efficient models used for sensor fusion technique in Autonomous Mobile Robots. The fundamentals of sensor fusion technique and the need to fuse sensor data for improved decision making and actuation are emphasized.