Aug 2026· International journal of computer information systems and industrial management applications· 0 citations
TL;DR
The system combines affordable hardware with smart sensor fusion and IoT connectivity to provide a scalable and cost-effective and reliable solution to modern smart industry-wide material transportation.
Abstract
The paper provides the design and implementation of sensor-fusion-guided mobile robotic vehicle in efficient and safe industrial material handling. The suggested system is implemented with the help of an Arduino Uno microcontroller with several sensors such as ultrasonic sensors, infrared (IR) sensors and wheel encoders to provide efficient perception and tracking of the environment. The fusion of these heterogeneous sensors is achieved through sensor fusion so that the weaknesses may be overcome, which allows the sensors to detect obstacles reliably, guide paths and navigate successfully in dynamic industrial settings. Ultrasonic sensors offer a range of distance measurements that are long, whereas IR sensors offer a high accuracy of short-range measurements, and the wheel encoders facilitate odometry-based estimation of movement. An ESP8266/ESP32 IoT chip is also installed in the robotic vehicle, which enables real-time tracking, assigning tasks remotely and visualizing the status of the system with the help of a cloud interface. The driver allows motor control, which is the L293D driver, and brings smooth and precise movements of wheels to move through the predetermined industrial paths autonomously. The solution suggested can greatly decrease the number of people on the work, eliminate the risks of collisions, and enhance the efficiency of the working process on the warehouse floor and factory premises. The system combines affordable hardware with smart sensor fusion and IoT connectivity to provide a scalable and cost-effective and reliable solution to modern smart industry-wide material transportation.
The paper compares the application characteristics of autonomous navigation in intelligent transportation, industrial logistics, and medical service robots, showing that different scenarios require different balances between robustness, efficiency, accuracy, safety, safety, and energy consumption.
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