Date of Award

6-3-2026

Document Type

Thesis

Publisher

Santa Clara : Santa Clara University, 2026

Departments

Computer Engineering; Computer Science and Engineering; Electrical Engineering; Electrical and Computer Engineering

First Advisor

Burak Kurkcu

Second Advisor

Angela Musurlian

Abstract

This project focuses on creating a locomotive device that is capable of movement without relying on active wheels. This kind of system is essential to exploration in rough terrains where wheel-based motion proves to be ineffective. Drawing inspiration from the natural movement of snakes- the animal most successful in traversing difficult and diverse environments- we will develop a modular snake-like robotic prototype. Our modular design will allow for simplified maintenance, easy component replacement, and opportunity for further development and research.

Our approach will integrate electronic circuits, obstacle awareness via live camera feed, and locomotion control programmed via serial protocols on a Raspberry Pi. Our overarching goal is to develop a locomotive strategy to efficiently and effectively navigate unexplored, rough terrain. Our approach to designing the wheelless snake-like robot follows a multidisciplinary and iterative engineering process that integrates mechanical design, embedded systems, and real-time software control. The system is divided into modular subsystems, allowing each component to be developed, tested, and improved independently before full system integration.

The mechanical structure of the robot is designed using CAD tools, where each segment is optimized for flexibility, durability, and ease of assembly. The modular design allows individual segments to be replaced or adjusted without requiring a complete redesign of the system, which improves maintainability and scalability. As shown in our system architecture (see Section III), each module contributes to the overall locomotion through coordinated actuation.

From an electronics perspective, each segment includes a microcontroller and servo motor, while the head module contains a Raspberry Pi responsible for higher-level control, image processing, and communication. Communication is implemented using UART serial protocol, enabling real-time modular control.

On the software side, we implement a sinusoidal locomotion algorithm inspired by biological snake motion. This algorithm generates phase-shifted signals across modules to produce forward motion. In parallel, we integrate a realtime object detection system using a camera and YOLO-based image processing, allowing the robot to detect obstacles and adjust its trajectory dynamically.

Our approach emphasizes modularity, adaptability, and real-time responsiveness. By combining simulation, hardware prototyping, and iterative testing, ensure that the final system is both functional and extensible for future research and development. The fully integrated robot snake system can successfully move across terrain and identify obstacles.

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