Spotlight on Research with Karinne Ramirez-Amaro

Abstract:

Autonomous robots are expected to learn new skills and to re-use past experiences in different situations as efficient, intuitive and reliable as possible. Robots need to adapt to different sources of information, for example, videos, robot sensors, virtual reality, etc. Then, to advance the research in the understanding of human activities, in robotics, the development of learning methods that adapt to different sensors are needed. In this talk, I will introduce a novel learning method that generates compact and general semantic models to infer human activities. This learning method allows robots to obtain and determine a higher-level understanding of a demonstrator’s behavior via semantic representations. First, the low-level information is extracted from the sensory data, then a meaningful semantic description, the high-level, is obtained by reasoning about the intended human behaviors. The introduced method has been assessed on different robots, e.g. the iCub, REEM-C, PR2, and TOMM, with different kinematic chains and dynamics. Furthermore, the robots use different perceptual modalities, under different constraints and in several scenarios ranging from making a sandwich to driving a car assessed on different domains (home-service and industrial scenarios). One important aspect of our approach is its scalability and adaptability toward new activities, which can be learned on-demand. Overall, the presented compact and flexible solutions are suitable to tackle complex and challenging problems for autonomous robots.

About the speaker:

Dr. Karinne Ramirez Amaro is an Assistant professor at Chalmers University of Technology since September 2019. Previously, she was a post-doctoral researcher at the Chair for Cognitive Systems (ICS) at the Technical University of Munich (TUM). She completed her Ph.D. (summa cum laude) at the Department of Electrical and Computer Engineering at the Technical University of Munich (TUM), Germany in 2015. From October 2009 until Dec 2012, she was a member of the Intelligent Autonomous Systems (IAS) group headed by Prof. Michael Beetz. She received a Master degree in Computer Science (with honours) at the Center for Computing Research of the National Polytechnic Institute (CIC-IPN) in Mexico City, Mexico in 2007. Dr. Ramirez-Amaro received the Laura Bassi award granted by TUM and the Bavarian government to conduct a one-year research project in December 2015. 

For her doctoral thesis, she was awarded the price of excellent Doctoral degree for female engineering students, granted by the state of Bavaria, Germany in September 2015. In addition, she was granted a scholarship for a Ph. D. research by DAAD – CONACYT and she received the Google Anita Borg scholarship in 2011. She was involved in the EU FP7 project Factory-in-a-day and in the DFG-SFB project EASE. Her research interests include Artificial Intelligence, Semantic Representations, Assistive Robotics, Expert Systems, and Human Activity Recognition and Understanding.

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About CHAIR Spotlight on Research​​​​​​
Chalmers AI Research Center, CHAIR Spotlight on Research is a series of AI short talks hosting researchers from Chalmers. The seminars are targeted towards experts from the Chair Consortium core partners as well as other Chalmers researchers.

The aim is to increase awareness of AI at Chalmers between Chalmers researchers and AI experts in industry. In the seminars, speakers present an overview of their current research and thoughts for new research, ideas, challenges – anything they believe to be of interest for other researchers. The seminar is taking place online and is scheduled to contain 30 minutes of presentation and 15 minutes of discussion. The seminars are open to all and are free of charge. CHAIR Spotlight Research talks are taking place on Fridays 13:00-13:45.

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