Remote Machine Intelligence Lab

What it is about

You learn the fundamentals and practical application of teleoperation, robot control with haptic feedback, as well as autonomous drone functions. By the end you can connect haptic devices with remote robots, realize stable force feedback, program teleoperation systems, and implement 3D occupancy mapping as well as planning for drones as a ROS/C++ real-time application.

What you will be able to do

Understand the operating principles of teleoperation systems with haptic feedback
Write code to connect haptic devices with remote robots and generate stable force feedback
Program teleoperation systems for remote interaction and skill transfer
Explain components of autonomous drones: state estimation, mapping, planning, control
Understand 3D occupancy mapping and planning and implement them as a real-time ROS/C++ application
Raise awareness for user-friendly and safe interaction

What the module consists of

VorlesungProvision of theoretical foundations in robotics, control, teleoperation and drones
Labor / PraktikumConducting several experiments and implementation tasks on robots, haptic devices and drones
Final Task / ProjektSynthesis and application of the learned methods in a complex concluding task with presentation

Teaching method

LehrvortragDirect transfer of theoretical knowledge
Lab assignments (praktische Übungen)Testing and applying learned methods in simulation and real systems
Final task mit PräsentationAssessment of the ability to transfer methods to a complex, realistic task

What you should already know

Fundamentals of control theoryrecommended
Fundamentals of roboticsrecommended
Fundamentals of mobile roboticsrecommended
Fundamentals of 3D computer visionrecommended
C, C++recommended
Pythonrecommended

Assessment

LaboraufgabenProgrammierungProject workPresentation

Performance is assessed through several laboratory tasks and a final project task. There are four laboratory tasks (each 15% of the total grade) and a final task (40%). Each lab task consists of: writing code/algorithms (5%), implementing on real systems (5%), solving the given problem (5%). The final task is assessed by: programming (10%), solving the complex task (25%), and final presentation (5%). Duration and tools are determined by the respective lab and project requirements.

Reading list

Siciliano, Bruno; Khatib, Oussama; Kröger, Torsten - Springer Handbook of Robotics
Hokayem, Peter F.; Spong, Mark W. - Bilateral teleoperation: A historical survey (Automatica, 2006)
Lee, Jae-young; Payandeh, Shahram - Haptic Teleoperation Systems - Signal Processing Perspective (Springer, 2015)
Chernova, S. Sonia; Thomaz, Andrea L. - Robot Learning from Human Demonstration (Springer, 2014)
Fox, D.; Thrun, S.; Burgard, W. - Probabilistic Robotics
Siciliano, Bruno et al. - Robotics: modelling, planning and control
Steinbach, E. et al. - Haptic Communications (Proceedings of IEEE, 2012)
Lawrence, Dale A. - Stability and transparency in bilateral teleoperation (IEEE Trans. on Robotics and Automation, 1993)
Nuño, Emmanuel; Basañez, Luis; Ortega, Romeo - Passivity-based control for bilateral teleoperation: A tutorial (Automatica, 2011)
Chen, Xiao et al. - On the Communication Channel in Bilateral Teleoperation: An Experimental Study for Ethernet, WiFi, LTE and 5G (IROS, 2022)

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Remote Machine Intelligence Lab

What it is about

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What the module consists of

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