Master Thesis in Enhancing Robot Navigation and Coverage Tasks by Moving Obstacles Autonomously

Company Description

At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people’s lives. Our promise to our associates is rock-solid: we grow together, we enjoy our work, and we inspire each other. Join in and feel the difference.

The Robert Bosch GmbHis looking forward to your application!

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 robot’s 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 first step it is assumed that the classification of moveable obstacles is given, but as a stretch also this classification 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 real-world 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 trade-off between driving and moving an obstacle.
• Furthermore, you will integrate the algorithm into a complete coverage pipeline and test it in a real-world setting using an existing robotic platform.
• You will extend the functionality to try to free the robot when it is stuck and implement a classification 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 C++17; 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)
+49 173 3608833

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Summary

• Type: Full-time
• Function: Education