Author(s): Lucas Ferreira Monteiro and Elena Rossi

Abstract: Low-cost mobile robots capable of avoiding obstacles are increasingly important in education, domestic automation, and small-scale industrial applications. However, many existing designs rely on expensive sensors, complex computation, or proprietary platforms that limit accessibility. This research presents the design and implementation of a low-cost obstacle avoidance robot using simple control algorithms and readily available electronic components. The proposed system integrates a microcontroller, ultrasonic distance sensors, DC motors, and a basic motor driver to achieve autonomous navigation in unknown environments. A rule-based control strategy is employed, where sensor feedback is processed through threshold-based decision logic to generate real-time motion commands. The hardware architecture emphasizes affordability, modularity, and ease of replication, while the software design prioritizes transparency and minimal computational overhead. Experimental evaluations were conducted in controlled indoor environments containing static obstacles of varying shapes and orientations. Performance was assessed using metrics such as obstacle detection accuracy, response time, path deviation, and overall system reliability. The results demonstrate that the robot successfully avoids obstacles with consistent performance, despite the absence of advanced mapping or learning algorithms. The findings indicate that simple control techniques can provide reliable autonomy when combined with appropriate sensor placement and mechanical design. This work highlights the feasibility of developing functional autonomous robots for learning and prototyping purposes without high financial or technical barriers. The proposed design can serve as a foundational platform for students and hobbyists, as well as a baseline system for further research on navigation, sensor fusion, and intelligent control. Future enhancements may include adaptive thresholding, energy optimization, and integration of additional low-cost sensors to improve robustness and versatility. Such systems also encourage hands-on understanding of robotics principles, embedded programming, and real-world constraints, fostering innovation and practical problem-solving skills among early-stage engineers and researchers. These outcomes support broader adoption in resource-limited educational and experimental settings.

DOI: 10.33545/27075923.2026.v7.i1a.122

Pages: 26-31 | Views: 104 | Downloads: 55

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