Lehrinhalte
[list]
[*]Further development and optimization of a robust C framework for solving non-trivial problems in the field of autonomous driving based on realistic challenges from the Carolo Cup, an international student competition for autonomous model cars
[*]Development and implementation of different algorithms (e.g., for motion planning, image processing, control, and obstacle avoidance) in an embedded system with hard real-time requirements and limited resources (memory, ...)
[*]Application and further development of control methods in the field of autonomous driving
[*]Application of software engineering techniques (design, documentation, testing, ...) for solving the problem
[*]Using source code management systems, time management and other project management tools
[*]Presentations of the project results
[/list]
Literature
[url]https://www.es.tu-darmstadt.de/lehre/aktuelle-veranstaltungen/ps-af-ii/[/url] und Moodle
Voraussetzungen
It is recommended to have successfully participated at the project seminar Autonomous Driving I
Official Course Description
Students learn to independently develop, implement and present new concepts and algorithms in the field of autonomous driving. Realistic problems from the Carolo Cup are solved with existing knowledge and skills practically and the implementation is ensured by quality assurance measures.
Students who have successfully participated in this project seminar are able to independently analyze and solve a complex and realistic task in the field of autonomous driving. The participants acquire the following skills in detail:
- Further development and optimization of an existing software system and the used algorithms independently
- Solving and implementation of non-trivial, realistic control engineering challenges
- Extensive use of tools for version, configuration, change, and quality assurance management
- Realistic time planning and resource allocation (project management)
- Further development and optimization of complex hardware/software systems under realistic environmental conditions
- Planning and implementation of extensive quality assurance measures
- Collaboration, communication and organization within the team
[list]
[*]Further development and optimization of a robust C framework for solving non-trivial problems in the field of autonomous driving based on realistic challenges from the Carolo Cup, an international student competition for autonomous model cars
[*]Development and implementation of different algorithms (e.g., for motion planning, image processing, control, and obstacle avoidance) in an embedded system with hard real-time requirements and limited resources (memory, ...)
[*]Application and further development of control methods in the field of autonomous driving
[*]Application of software engineering techniques (design, documentation, testing, ...) for solving the problem
[*]Using source code management systems, time management and other project management tools
[*]Presentations of the project results
[/list]
Literature
[url]https://www.es.tu-darmstadt.de/lehre/aktuelle-veranstaltungen/ps-af-ii/[/url] und Moodle
Voraussetzungen
It is recommended to have successfully participated at the project seminar Autonomous Driving I
Official Course Description
Students learn to independently develop, implement and present new concepts and algorithms in the field of autonomous driving. Realistic problems from the Carolo Cup are solved with existing knowledge and skills practically and the implementation is ensured by quality assurance measures.
Students who have successfully participated in this project seminar are able to independently analyze and solve a complex and realistic task in the field of autonomous driving. The participants acquire the following skills in detail:
- Further development and optimization of an existing software system and the used algorithms independently
- Solving and implementation of non-trivial, realistic control engineering challenges
- Extensive use of tools for version, configuration, change, and quality assurance management
- Realistic time planning and resource allocation (project management)
- Further development and optimization of complex hardware/software systems under realistic environmental conditions
- Planning and implementation of extensive quality assurance measures
- Collaboration, communication and organization within the team
- Lehrende: Eric Lenz
- Lehrende: Andreas Schürr
Semester: ST 2021