Abstract
Autonomous vehicle research often requires expensive hardware platforms equipped with multiple sensors, which limits accessibility for students and early-stage researchers. To address this challenge, this paper presents the design and implementation of a low-cost autonomous robot car using a Raspberry Pi integrated with an AI-based voice assistant. The proposed system enables autonomous navigation, obstacle detection, fog-aware vehicle detection, multilingual voice control, and automatic parking. Sensor fusion is achieved using ultrasonic sensors, camera modules, and optional thermal sensing to ensure safe operation in low-visibility conditions. Voice commands primarily in English are processed using a cloud-based speech recognition service, allowing natural human–vehicle interaction. The system architecture is modular, enabling gradual sensor integration and future scalability. Experimental results demonstrate reliable obstacle avoidance, accurate voice command execution, and successful autonomous parking, validating the effectiveness of the proposed platform as a practical testbed for intelligent transportation research.The rapid development of autonomous driving technologies has emphasized the need for affordable and scalable experimental platforms capable of validating perception, decision-making, and control algorithms in real-world conditions.
Keywords
Autonomous Robot Car, Raspberry Pi, AI Assistant, Voice Control, Speech Recognition, Auto Parking.
Citations
IRE Journals:
Prajwal Pachpande, Raj Khandekar, Abhay Barathe, Prathamesh Bhoir, Dr. Pranita Potey "Raspberry Pi-Based Automated Robot Car with an AI Assistant" Iconic Research And Engineering Journals Volume 9 Issue 9 2026 Page 1324-1329 10.64388/IREV9I9-1715217
IEEE:
Prajwal Pachpande, Raj Khandekar, Abhay Barathe, Prathamesh Bhoir, Dr. Pranita Potey
"Raspberry Pi-Based Automated Robot Car with an AI Assistant" Iconic Research And Engineering Journals, 9(9) 10.64388/IREV9I9-1715217
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