Teleoperation is a very vast field that stretches over many different disciplines, including computer science, engineering, control theory, and many more. A teleoperation scenario can be defined when a device, e.g., a machine, robot manipulator or mobile robot, is being controlled by a human operator who is located in a different location than the device. Both parts are connected by a communication channel that transports the desired control input from the operator to the device and the sensor readings from the device back to the operator.
I am investigating teleoperation setups, where the operator controls a remote aircraft, namely a multirotor unmanned aerial vehicle (UAV) capable of vertical takeoff and landing (VTOL). The UAV is controlled using input devices that can also be found in regular planes and helicopters. Visuals typically include cockpit instruments and displays, plus live video streams delivered by one or more cameras attached to the UAV.
The separation of the operator from the aircraft adds additional challenges to the already demading task of controlling said aircraft. This is mainly due to the charateristics of the channel used between the operator and the UAV. Low overall channel capacity, latencies, noise, and jitter are the main factors that degrade the quality of controlling the UAV.
One reason for this can be the lack of information decreases the sense of "being there". This lack of situational awareness (SA) inevitably leads to a worsened performance in controlling the UAV and, in the worst case, the UAV to crash. Having said that, increasing the channel capacity or adding new sources of information should lead to a better SA and performance of the operator. My hypothesis is that presenting the motion of the UAV to the operator as feedback cue adds to the overall channel capacity. Therefore, the performance of the operator should increase.
However, it is not clear how the motion feedback needs to be defined in order to maximize the performance. In some cases motion feedback might even pose as a source of disturbance for the operator, worsening the performance.
In my PhD thesis I investigate the impact of motion feedback cues on operator performance. I hope that I can find initial evidence that suport my hypothesis that motion feedback helps increasing operator performance in some teleoperation scenarios.
I have been working on a simulation environment called SwarmSimX. SwarmSimX is used within the HRI Group as a development and testing environment for a group of micro aerial vehicles (MAV). The focus of SwarmSimX is to provide a highly modular simulation framework that allows for simulating physical and visual properties of a virtual environment in real-time.
Below you can see a video of a quadcopter flying in the Multi-Agent-Lab (MAL) of the Max-Planck-Institute for Biological Cybernetics. The quadcopter is controlled by a program that uses the desired position and velocity of a recorded flight of a real quadcopter as control input.
Diploma Thesis "Development of a Real-Time Simulation Environment for multiple Robot Systems"
Working as an undergraduate research assistant in the HRI Group at the Max-Planck-Institut for Biological Cybernetics.
Implementation of a communication interface to be used in Simulink models controlling the Cybermotion Simulator.
Implementation of a program acting as a virtual Cybermotion Simulator for testing and validation purposes.
|- 2003||High School (Abitur)|
|2003 - 2004||Civilian service|
|2004 - 2012||
Eberhard Karls-University of Tübingen
Conference papers (4):
, , , , , and (May-2013) Interactive Demo: Haptic Remote Control of Multiple UAVs with Autonomous Cohesive Behavior ICRA 2013 Workshop Towards Fully Decentralized Multi-Robot Systems: Hardware, Software and Integration, 1-3.
, , and (May-2013) SwarmSimX and TeleKyb: Two ROS-integrated Software Frameworks for Single- and Multi-Robot Applications ICRA 2013 Workshop Towards Fully Decentralized Multi-Robot Systems: Hardware, Software and Integration, 1-3.
, , and (November-2012) SwarmSimX: Real-time Simulation Environment for Multi-robot Systems In: Simulation, Modeling, and Programming for Autonomous Robots, 3rd International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR 2012), Springer, Berlin, Germany, 375-387.
, , and (May-2010) Visual-Vestibular Feedback for Enhanced Situational Awareness in Teleoperation of UAVs In: AHS International 66th Annual Forum, 66th American Helicopter Society International Annual Forum 2010, AHS International, Alexandria, VA, USA, 2809-2818.