Master thesis: safety and performance for collaborative robotics in smart manufacturing
Machine Intelligence and Automation is a research area at Ericsson Research. Our mission is to drive machine intelligence thought leadership to automate and transform Ericsson offerings and operations and to enable emerging business. This includes development of models, frameworks and infrastructure where we in our advancements push the technology frontiers. We engage in both academic and industry collaborations and drive the digitalization of Ericsson and the Industry by developing state of the art solutions that simplify and automate processes in our products and services and create new value through data insights.
The Cognitive Automation Lab group at Ericsson Research in Stockholm is a research group within the Machine Intelligence and Automation research area working on all aspects of artificial intelligence, such as knowledge representation, deduction, reasoning and problem solving, image processing, natural language processing, automated planning and applied machine learning. We are currently looking for several master thesis students that will work on different problems related to safety and performance for collaborative robotics in smart manufacturing. In particular, in an automated warehouse where autonomous robots load trucks with products while sharing the same environment with humans, a proper safety analysis is performed to avoid the hazardous situations without compromising the productivity. We have a basic safety analysis mechanism using image processing for object identification and risk assessment and mitigation to provide safety. The tasks of this thesis will be to extend the safety model: (1) adding safety from communication perspective i.e. among robots and between the robot and the Cloud, and (2) performing highly-computational processing in cloud.
- Literature review, identifying relevant concepts and algorithms for safety analysis and image processing involving communication between robot and the cloud.
- Propose a suitable safety analysis technique for collaborative robots using cloud-based and D2D communications.
- Model and implement the technique for different scenarios of the selected use case.
- Potentially use/link to a simulating environment and real robots for testing the software for the presented use case.
- Performance evaluation for cloud-based and d2d scenarios involving image processing.
We are looking for open-minded students who seek a challenging research work with the freedom to propose and develop your own ideas. To be successful in this thesis work the candidate(s) would need the following:
- MSc studies in Computer Science, Electrical and Computer Engineering or similar area.
- Excellent programming skills in C/C++, or Python or Java or Matlab.
- Good knowledge of concepts in machine learning (e.g. deep learning), robotics, ROS, etc.
- Experiences with machine learning libraries Tensor flow, Keras, sci-kit learn etc.
- Knowledge of safety analysis techniques, risk assessment algorithms, communication protocols is a bonus
- Like to build end to end prototypes and concepts
- Be fluent in English
In case of questions, please contact: Rafia Inam: email@example.com
Klaus Raizer: firstname.lastname@example.org
Alberto Hata: email@example.com
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Primary country and city: Sweden (SE) || || Stockholm || IT
Req ID: 261138