💡 MUSE: Our Innovative Project 💡
We are thrilled to share with you an overview of our MUSE project, on which we have worked with an incredible team dedicated to advancing automotive technologies. 🎉
🌟 Objectives of the MUSE Project:
The MUSE project aims to enhance the field of automotive technologies by developing a multimodal sensing environment for mobile applications. This includes creating decision-support software to optimize sensor selection for autonomous vehicles, based on a driving simulator producing multimodal signals (LIDAR, radars, cameras, OBD2, etc.). The project focuses on establishing an interactive loop to optimize the choice and positioning of multimodal sensors through realistic simulations. Additionally, it utilizes multimodal transformer-based learning for precise recognition in various use cases.
The MUSE project is structured around use cases that include collecting and analyzing data from moving passengers to adapt vehicle equipment, testing external sensors to optimize the safety and performance of autonomous vehicles, and simulating V2X interactions to improve communication and road infrastructure safety, especially for priority vehicles like ambulances.
👥 Meet the Team:
Lucas El Raghibi is the project manager, overseeing all project activities and ensuring smooth coordination among all team members and stakeholders.
Chun Siu Chan and Yen-Chieh Chuang focus on LIDAR equipment, operations management, data preprocessing, and system integration to ensure accurate environmental mapping.
Yeong Chi Hsu and Zhen-Yu Chen are responsible for camera systems, including installation, image processing, and system environment setup for optimal performance.
🚀 Current Progress:
- Successful integration of LIDAR, camera, and OBD2 systems
- Successful visualization of LIDAR data
- Development of data collection and processing programs for sensors
- Development of an AI model to blur license plates and human faces
The OpenHub provides the necessary materials and equipment to develop and implement these technologies, facilitating the deployment of solutions proposed by the MUSE project. The project is supported by Service public de Wallonie and involves several industrial and academic partners, including AISIN Europe, Université catholique de Louvain, UMONS, and Multitel, each bringing complementary expertise to achieve the project’s objectives. Expected outcomes include the validation of multimodal sensors in diverse scenarios, the development of advanced AI models for decision support, and the demonstration of the effectiveness of V2X communication systems.
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