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@article{208523,
        author = {Shivraj Padmakar Shinde and Dr. Kirankumar Premchand Johare},
        title = {An Affordable Six-Wheel Arduino Rover for Hands-On Learning in Planetary Robotics and Environmental Sensing with A Path Toward Edge AI},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {no},
        pages = {345-357},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=208523},
        abstract = {This work reviews recent literature (2021–2026) on low-cost rover platforms, educational robotics, six-wheel mobility, environmental sensing, and embedded machine learning, and positions an affordable six-wheel Arduino rover within this landscape. The platform pairs an Arduino Uno with six DC geared motors driven through an L298N dual H-bridge, while an HC-05 Bluetooth module links the chassis to an Android handset for basic teleoperation. A modular sensing bay can accommodate the DHT11 temperature-humidity sensor, the BMP280 barometric sensor, the HC-SR04 ultrasonic ranger, soil-moisture and light probes, MQ-series gas detectors, and the MPU6050 inertial unit. The chassis is designed in CAD for fabrication from acrylic sheet, keeping the projected build cost within a few thousand Indian rupees.
The review synthesises peer-reviewed literature indexed in major scholarly databases, supplemented by an authenticated NASA technical memorandum, spanning flight autonomy on Perseverance, deep-learning terrain classification, rocker-bogie suspension optimisation, low-cost sensor calibration, and meta-analytic findings on robotics-supported learning. 
Five recurring management concerns emerge: purpose, hardware, sensing, process, and reliability. We organise these into a development framework for student-built rovers and map a staged upgrade path toward future TinyML inference, autonomous obstacle avoidance, GPS-assisted navigation, and IoT telemetry. AI is therefore positioned as a future capability rather than a demonstrated onboard function, with the present design providing the sensing, control, and data-acquisition foundation for subsequent TinyML deployment. The platform is an educational terrestrial rover, not flight-qualified planetary hardware. The literature supports hands-on robotics as a means of developing computational thinking and STEM engagement, while the proposed platform provides a practical setting for such learning.},
        keywords = {Artificial Intelligence; Arduino Uno; Six-Wheel Rover; Planetary Robotics; Environmental Sensing; Bluetooth Control; Embedded Systems; Educational Robotics; TinyML},
        month = {September},
        }