Week 1: Project Motivation and Design Approach

Smart Obstacle Avoidance Helmet Development Log - Week 1: Project Motivation and Design Approach

Project Background and Motivation

In daily life, visually impaired individuals often face risks of injury due to obstacles, while safety concerns are also prominent in industrial environments and cycling scenarios. Traditional guiding canes, although effective, have limitations in complex environments, especially in detecting high-level obstacles such as hanging objects, tree branches, and signboards, as well as sudden unexpected obstructions. To address these challenges, we propose the development of a smart obstacle-avoidance helmet that enhances obstacle detection capabilities for visually impaired individuals and people navigating complex work or daily environments.

Our inspiration comes from automotive radar technologies used in autonomous driving systems, such as Tesla’s Autopilot and Baidu Apollo. These systems leverage multiple sensors and intelligent algorithms to perceive the surrounding environment and assist or even replace human decision-making in real-time. Our goal is to miniaturize these technologies and apply them to personal mobility scenarios, ensuring safer travel and daily activities for users.

Currently available obstacle avoidance devices mostly rely on handheld or waist-mounted solutions, which restrict movement and fail to protect the head region. Our smart helmet aims to detect obstacles around the user through sensor-based environmental perception and provide feedback through audio alerts, reducing collision risks and preventing accidents.

Project Objectives

The primary goal of this project is to design and implement a smart helmet capable of real-time obstacle detection and intuitive feedback via auditory alerts. Specific objectives include:

• Accurate Distance Measurement: Detect obstacles within safety range.
• Timely Feedback: Provide directional sound-based feedback for enhanced situational awareness.
• High Comfort Level: Support 3D-printed customization to ensure a comfortable fit without interfering with daily activities.
• Energy Efficiency: Ensure low power consumption and the use of minimal, recyclable materials.

Technical Approach

To achieve the above objectives, we plan to employ the following technical solutions:

1. Sensor Selection

   • ToF400C infrared laser ranging module for precise distance measurement.

2. Processing Unit

   • STM32 microcontroller as the core processing unit to handle sensor data and control the feedback system.

3. Feedback System

• A buzzer producing different directional sounds to indicate obstacle positions.
• A voice module for auditory alerts, improving user experience.

Why ToF instead of Ultrasonic Sensors?

Initially, we considered using ultrasonic sensors for distance measurement. However, we found that they had certain accuracy limitations in environments with glass surfaces or narrow spaces, and their detection angle was relatively wide, making precise obstacle avoidance challenging. ToF (Time-of-Flight) sensors, on the other hand, measure distances using light pulses, providing higher accuracy and more stable performance across different environments. For this reason, we decided to use the ToF400C sensor as our primary distance measurement module.

Why STM32 instead of Arduino?

In the early design phase, we considered using Arduino because of its ease of use and strong community support. However, we encountered limitations when trying to handle multiple ToF sensors simultaneously. Arduino lacks strong parallel clocking capabilities, leading to potential delays in sensor readings. STM32, on the other hand, supports parallel clocking, allowing us to control multiple ToF sensors at the same time, ensuring faster response and better real-time obstacle detection. Additionally, STM32 offers more flexible PWM control and low-power modes, making it a more efficient choice. Based on these advantages, we decided to use STM32 as our main microcontroller.

Anticipated Challenges

Although the project framework is well-defined, several technical challenges may arise during development, including:

• Distance Measurement Accuracy and Error Control: TOF400C sensors require optimization to ensure reliable distance measurement under various conditions.
• Complex STM32 Development: Hardware compatibility, pin configurations, and driver setups may pose difficulties in programming and debugging.
• 3D Modeling Complexity: Proficiency in modeling software is required to ensure that the designed model meets real-world assembly requirements.

Conclusion

During the first week, our focus has been on defining project requirements, establishing the technical framework, and identifying potential challenges. In the second week, we will begin 3D modeling, circuit design, and component soldering, laying the foundation for subsequent software development and system integration.