Topics Advanced Seminar & Projektpraktikum SS20

Due to the current situation, all topics for the Advanced Seminar and Projektpraktikum are listed here. There will be no physical meeting to introduce the topics.

Please get in touch with contact peron listed directly in the description of the topic to discuss any details or ask questions.

Advanced Seminar topics are listed here, Projektpraktikum topics are listed in the subpage.

Topics Advanced Seminar

Causality in Artificial Cognitive Systems (already taken)

Advisor: Nicolas Berberich and Constantin Uhde

Classical supervised machine learning is focused on learning associations between variables. If two events or features are frequently observed together then observing one changes the likelihood of observing the other. For efficient action planning, a cognitive system is required to not only learn bidirectional associations but also which event causes the other event, such that it can perform the right interventions to reach its goal. This task falls under the topic of “causal inference” which gained popularity in the last years due to work by Judea Pearl, Joshua Bengio, Bernhard Schölkopf and others. The aim of this seminar project is to produce a synopsis of state-of-the-art research in causal learning for artificial cognitive systems and robotics.  

References:

  • David Vernon, “Artificial Cognitive Systems: A Primer”  

  • Judea Pearl, “Causal Inference in Statistics: A Primer” 


Sensors for Prosthetic Hands to Support Sensory Feedback (already taken)

Advisor: Nicolas Berberich

Abstract: The goal of this seminar project is to critically analyze state-of-the-art research on the development of sensors for prosthetic hands. A special focus should be put on which sensor modalities are included, where the sensors are placed on the prosthetic hand and how the measured sensor values are used for sensory feedback to the prosthesis user. Methodologically, it is furthermore important to review how the sensors are scientifically evaluated, e.g. through objective performance tests or subjective user feedback. 

References:

  • Jaemin Kim et al. “Stretchable silicon nanoribbon electronics for skin prosthesis”, Nature Communications, 2014 

  • Jacob Segil et al. ”Multi-modal prosthetic fingertip sensor with proximity, contact, and force localization capabilities”, Collaborative and Controllable Robotics for Biomedical and Industrial Applications – Research, 2019 

  • Ahmad Alhaddad et al. “Toward 3D printed prosthetic hands that can satisfy psychosocial needs: grasping force comparisons between a prosthetic hand and human hands”, International Conference on Social Robotics, 2017 

 


State of the art of “Robocup@Home” and “World Robot Summit” solutions

Advisor: Julio Rogelio Guadarrama Olvera

The Robocup@Home competition is a world tournament on human service robotics solutions. It started as a side event of the Robo Cup football competition and has built its own community and enthusiasts over the years. Nowadays, there are several local leagues around the world that help improve the solutions under different conditions and challenges which are then tested in the world league. The aim of this topic is to find out how are implemented the solutions of the winner teams (1st, 2nd, and 3rd place) in the world and local leagues to help our team with fresh ideas. The research work will include both reading team description papers and open-source code when available.

References:

 


State of the art in walking controller software architectures

Advisor: Julio Rogelio Guadarrama Olvera

Biped and humanoid robots are complex systems that have gained popularity in recent decades. The tasks of keeping balance and walking require precise real-time implementations for estimating the robot state, generating walking trajectories, rejecting external disturbances, and navigating in static or changing scenarios. Such implementations can be found in open source projects and commercial software stacks that adapt to the needs of specific humanoid and biped robot models. The aim of this topic is to compare the latest implementations of walking controllers to find out their advantages and disadvantages for both small and human size robots. 

References:

  • Kajita, S., Hirukawa, H., Harada, K., & Yokoi, K. (2014). Introduction to humanoid robotics (Vol. 101, p. 2014). Springer Berlin Heidelberg. 

  • Natale, L., Asfour, T., Kanehiro, F., & Vahrenkamp, N. (Eds.). (2018). Software Architectures for Humanoid Robotics. Frontiers Media SA. 

  • Englsberger, J., Ott, C., & Albu-Schäffer, A. (2015). Three-dimensional bipedal walking control based on divergent component of motion. Ieee transactions on robotics, 31(2), 355-368. 

  • Caron, S., & Kheddar, A. (2016, November). Multi-contact walking pattern generation based on model preview control of 3d com accelerations. In 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids) (pp. 550-557). IEEE. 


State of the art in humanoid telerobotics 

Abstract: Remote controlling robots is a complex task. Providing means of controlling a robot with your own body movement can make this control much more intuitive. 
The transfer of human motion to a humanoid robot however falls under the "correspondence problem" of embodiment. The mapping is not perfect and requires adapting signals to the changed morphology. 
In this advanced seminar, you will explore the state of the art in human motion transfer to humanoid robots and summarize achievements, shortcomings and potential research directions. 

References:

  • Telerobotics et al. “Springer Handbook of Robotics: Chapter 31.” (2008).  

  • Macchini, Matteo et al. “Personalized Telerobotics by Fast Machine Learning of Body-Machine Interfaces.” IEEE Robotics and Automation Letters 5 (2020): 179-186. 

  • Goodrich, Michael A. et al. “Teleoperation and Beyond for Assistive Humanoid Robots.” (2013) 

  • Bauer, Adrian S. et al. “Inferring Semantic State Transitions During Telerobotic Manipulation.” 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2018): 1-9. 


Robots to support Society against Pandemics

Advisors: Nicolas Berberich & Constantin Uhde 

Abstract: Pandemics such as the current COVID-19 require strict physical distancing, e.g. through staying at home. As a result, many important tasks cannot be fulfilled by humans. However, new developments in many different fields of robotics might support society to lessen the impact.  The goal of this seminar topic is to explore how robots are already used to fight pandemics, which research directions are most promising and how robots might contribute in the future to better control the social and economic impacts of pandemics. Possible examples are telerobotics for remote working in manual jobs, disinfection robots, robots in hospitals and social robots for isolated elderly.  

References:

 


State of the art in Distributed Sensor Selection Algorithms (already taken)

Advisor: Quentin Leboutet

Abstract: Nowadays, multiple approaches to the estimation of high-order motion derivatives for innovative control applications, rely on the data collected by redundant arrays of inertial sensors mounted on robots, with promising results. However, most of these works suffer scalability issues induced by the considerable amount of data generated by such large-scale distributed sensor systems. A possible approach to tackle this issue is to use the data of a subset of sensors, selected among a larger collection of inertial sensing elements covering a rigid robot link. The sensor selection process is usually formulated as a combinatorial optimization problem, and solved – possibly online – using dedicated algorithms. During this advanced seminar, you will explore the state of the art in sensor selection algorithm, compare the main existing approaches, and investigate potential research directions.

References:

  • Joshi, Siddharth and Boyd, Stephen, “Sensor selection via convex optimization”, IEEE Transactions on Signal Processing (2008) 

  • Shamaiah, Manohar and Banerjee, Siddhartha and Vikalo, Haris, “Greedy sensor selection: Leveraging submodularity”, IEEE conference on decision and control (CDC) (2010) 

  • Hashemi, Abolfazl and Ghasemi, Mahsa and Vikalo, Haris and Topcu, Ufuk, “A randomized greedy algorithm for near-optimal sensor scheduling in large-scale sensor networks”, Annual American Control Conference (ACC) (2018)