Master Thesis in Enhancing Robot Navigation and Coverage Tasks by Moving Obstacles Autonomously
Master Thesis in Enhancing Robot Navigation and Coverage Tasks by Moving Obstacles Autonomously
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Job Description
Robots are increasingly used in unstructured environments such as homes and factories where they are required to navigate the environment reliably and efficiently. Among other tasks mobile robots are expected to perform coverage when it comes to tasks like cleaning inspection or the likes. Common metrics for coverage tasks are the time it takes to cover the area the distance traveled and the percentage of the area that has been covered. Current robots struggle at navigating in particularly cluttered environments where they drive suboptimal trajectories to avoid obstacles and in the worst case they get stuck due to the lack of space to drive to the next goal and trigger recovery strategies to free themselves.
The objective of this thesis is to develop an algorithm that alternates the execution of driving and pushing skills to increase coverage and move obstacles that might be on the robots way. This may also include deciding for pushing obstacles a bit out of the way when the robot gets stuck to free itself again. The algorithm should be able to decide when and where the robot should move an obstacle and minimize the number of times such an action is required. In a rst step it is assumed that the classication of moveable obstacles is given but as a stretch also this classication functionality can be part of the thesis. Additionally an algorithm that performs the moving action should be implemented to be integrated into a robotic platform and the capabilities of the developed algorithm should be demonstrated in a realworld scenario.
- During your thesis you will conduct a comprehensive literature review of existing coverage solutions in cluttered environments.
- You will design an algorithm that computes the tradeo between driving and moving an obstacle.
- Furthermore you will integrate the algorithm into a complete coverage pipeline and test it in a realworld setting using an existing robotic platform.
- You will extend the functionality to try to free the robot when it is stuck and implement a classication functionality to decide if obstacles are moveable.
- Finally please note that for the thesis you will have to look for a supervising professor at your university.
Qualifications :
- Education: Master studies in the field of Computer Science Robotics Artificial Intelligence or comparable with good grades
- Experience and Knowledge: in Python and C17; knowledge of ROS; experience with Behavior Trees is a strong plus
- Personality and Working Practice: you demonstrate strong motivation by tackling challenges enthusiastically and collaborating effectively with team members
- Languages: fluent in English
Additional Information :
Start: according to prior agreement
Duration: 6 months
Requirement for this thesis is the enrollment at university. Please attach your CV transcript of records examination regulations and if indicated a valid work and residence permit.
Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore we welcome all applications regardless of gender age disability religion ethnic origin or sexual identity.
Need further information about the job
Michaela Klauck (Functional Department)
#LIDNI
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
