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Undergraduate Research - Self-Driving Car Model Development
I conducted research for developing machine learning models for a self-driving car, while redesigning the APSC 258 machine learning course for year 2 students.
Industry
Industry
Programming
Programming
Hours
Hours
23
23
Skills
Skills
Simulator, Colab, Python
Simulator, Colab, Python
Simulator, Colab, Python
Challenge
The project aimed to simulate the complex movements and object-handling capabilities of UGV in a controlled virtual environment. Key challenges included achieving realistic physics for object interaction, programming autonomous navigation paths, and managing the real-time control of the robotic arm. The simulation required a precise balance between performance and realism to accurately mimic potential real-world applications, such as logistics and automated material handling. Additionally, incorporating C# for control logic demanded attention to optimization to ensure smooth, responsive performance.
Results
The completed simulation delivers a fully functional UGV with a robotic arm capable of autonomous navigation and precise object manipulation. This simulation provides a realistic testing ground for UGV applications in warehousing and logistics, allowing for safe experimentation and prototyping. The successful deployment of the simulation demonstrates its potential to accelerate the development of real-world UGV systems, enhancing efficiency and reducing operational costs.
Check out the test in my Youtube Channel!
Challenge
The project aimed to simulate the complex movements and object-handling capabilities of UGV in a controlled virtual environment. Key challenges included achieving realistic physics for object interaction, programming autonomous navigation paths, and managing the real-time control of the robotic arm. The simulation required a precise balance between performance and realism to accurately mimic potential real-world applications, such as logistics and automated material handling. Additionally, incorporating C# for control logic demanded attention to optimization to ensure smooth, responsive performance.
Results
The completed simulation delivers a fully functional UGV with a robotic arm capable of autonomous navigation and precise object manipulation. This simulation provides a realistic testing ground for UGV applications in warehousing and logistics, allowing for safe experimentation and prototyping. The successful deployment of the simulation demonstrates its potential to accelerate the development of real-world UGV systems, enhancing efficiency and reducing operational costs.
Check out the test in my Youtube Channel!
