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Bosch Future Mobility Challenge (BFMC) — Team Autonomists

This repository contains the software architecture, embedded firmware, and mechanical designs developed by Team Autonomists for the Bosch Future Mobility Challenge. The project focuses on the development of a 1:10 scale autonomous vehicle capable of real-time perception, localized decision-making, and V2X communication.

Technical Architecture

The system utilizes a distributed computing model, split between a high-level processing unit (Raspberry Pi/PC) and a low-level microcontroller (STM32 Nucleo).

1. Perception Module

  • Lane Detection (LD): Computer vision algorithms for track boundary identification and ego-lane positioning.
  • Object Identification: Convolutional Neural Networks (CNN) for real-time classification of traffic signs, obstacles, and pedestrian markers.

2. Control Module

  • State Machine: High-level logic for intersection handling and traffic rule compliance.
  • Kinematic Modeling: Calculation of required steering angles and longitudinal velocity.
  • Signal Processing: PID control loops for stabilizing motor output and servo positioning.

3. Connectivity Module

  • V2X Communication: Integration with the Bosch Environmental Server via MQTT/TCP-IP protocols.
  • Localization: Processing of global positioning data and traffic light status provided by the server infrastructure.

4. Embedded Platform (Firmware)

  • Actuation: Low-level PWM generation for the BLDC motor and steering servo.
  • Sensor Feedback: High-frequency interrupt handling for rotary encoders and IMU data acquisition.

Repository Structure

Team_Autonomists/
├── src/                    # High-level processing (Python/C++)
│   ├── perception/         # Image processing and inference scripts
│   ├── control/            # Trajectory planning and decision logic
│   └── connectivity/       # Server-side communication scripts
├── firmware/               # STM32 Nucleo source code and binaries
├── 3dp/                    # CAD source files and STL geometries
├── models/                 # Trained weights and model definitions
├── docs/                   # Technical specifications and schematics
├── main.py                 # System integration and execution entry point
└── requirements.txt        # Dependency specification

Team Autonomists

Name Role
Dhyumaan Raval team lead, computer vision and AI/ML systems, vehicle control, CAD designer
Meet Jain sensor fusion, microcontroller, communication protocols, github, firmware
Saumy Patel mechanics optimization, sensor integration, vehicle control, CAD designer
Chintan Trivedi data handling, communication protocols, data curator
Harshid Rawal computer Vision and AI/ML systems, rpi related operations

Acknowledgments

Thanks to Bosch Engineering Center Cluj and the BFMC organizers for creating a platform that allows students to explore real-world autonomous driving challenges.