Abstract-The successes of teleoperation scenarios for mobile robots depends on a stable and reliable communication link. The environment information collected by the robot -represented by 2D or 3D images -has to be provided with a high resolution and a low delay to ensure a fast and precise system response. But in most realistic applications, the communication parameters fluctuate strongly over time. It is necessary to monitor the communication link continuously to react in case of reduced bandwidth and increased delay.But which environment information and correspondingly which bandwidth is necessary to control a robot safely? Due to a missing reliable rule set we investigated this question for a UAV scenario based on two different environment representations (camera images, gridmaps). We designed a simulator based study and evaluated the capability of the participants to control a robot in case of delayed or coarsely rasterized information. Although our study involved only non-experts, we found some interesting first results. While the performance of our participants correlates strongly with the delay, it is nearly uncorrelated with the image resolution, which suggests downsampling as a valid response for bandwidth decrease. We also found that participants generally struggle with using grid map for controlling the robot. However, this type of interfaces requires far less bandwidth than images. They also excel in situations with higher delays, which makes them the tool of choice when there are really bad channel conditions.

The societal mission of mitigating air pollution and greenhouse gas emissions are forcing urban agglomerations worldwide strongly greening their urban transportation systems. The global megatrend of urbanization aggravates those challenges by steadily increasing the demand for urban movements of people and goods. Recent research concludes that the autonomous cars propagated in this context carry the risk of significant rebound effects and therefor make the overall societal benefit appear at least doubtful [Fraedrich et al. 2017; Hörl et al. 2019]. Shared autonomous fleets of electrically powered micro-vehicles, on the other hand, have the potential to reduce emissions through their electric powertrains, to avoid traffic jams by substituting of passenger cars, to achieve a high degree of comfort and flexibility compared to the classic car through automated provision and at the same time strengthen public transport as integrated last mile service. At the same time, micro-vehicles, for example in the form of cargo bikes, can be tailored very variably to a specific usage scenario to exploiting further efficiency gains. The authors propose a use case in which an electrified three-wheeled cargo bike, flexibly called to any location at any time, is provided in an automated manner and can be transferred to manual operation after being handed over to the user. After use, the vehicle is released and returns to the depot or is ready for the next request. The separation into automated provision and manual mobility service simplifies the safety concepts and functional safety of the system and thus, from the authors' point of view, increases the realization potential compared to the privat autonomous vehicles (PAV) or shared autonomous vehicles (SAV). The technical implications of this scenario are very similar to those of the autonomous car, but in some cases address significantly different focus, as the article will show. This paper describes the approaches developed during the prototypical realization of the usage scenario and presents proposals for solutions. For this purpose, first relevant requirements are defined, the existing vehicle and sensor concept are described in detail, and solutions for environment perception, prediction, localization, trajectory planning, and interaction design as well as for the confection of the overall logistics system are presented and evaluated in a simulative or experimental manner.

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The successes of teleoperation scenarios for mobile robots depends on a stable and reliable communication link. The environment information collected by the robot -represented by 2D or 3D images -has to be provided with a high resolution and a low delay to ensure a fast and precise system response. But in most realistic applications, the communication parameters fluctuate strongly over time. It is necessary to monitor the communication link continuously to react in case of reduced bandwidth and increased delay. But which environment information and correspondingly which bandwidth is necessary to control a robot safely? Due to a missing reliable rule set we investigated this question for a UAV scenario based on two different environment representations (camera images, gridmaps). We designed a simulator based study and evaluated the capability of the participants to control a robot in case of delayed or coarsely rasterized information. KeywordsUAV teleoperation; remote-controlled robots; user interface design MOTIVATIONRemotely controlled robots are widely used in industry, disaster management or in medical scenarios. Each remote robot scenario represents a closed loop control application. Sensors attached to a robot generate the input information for the operator. He reacts on the received environment data and provides commands via different interfaces. For this task, the operator needs to receive all relevant information in an appropriate format. In many applications the environment situation is reflected by either using (multiple) video streams, or by transmitting whole (3D) maps to the operator's desk, representing a cumulated sensor information over time. Depending on the dynamics of the controlled system and its environment, we have to consider constraints within the con- * This work was partially supported by the German Research Foundation (DFG) research project "MoCoRo Plattform für mobile kooperative Robotik" Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). trol loop that are induced by the communication channel. In case of a long delay the robot is not able to move with high velocity, to avoid occurring obstacles or to interact precisely with the surroundings. In case of limited bandwidth the video streams have to be downsampled or compressed. The aspects of communication bandwidth and delay are strongly connected with the communication configuration. Especially in ad-hoc scenarios (e.g. disaster robotics [4]) the communication bandwidth is limited, varies over time and does not ensure a specific response time. This is especially true for the operation of Unmanned Aerial Vehicles (UAV) which neccessarily depend on error-prone wireless communication link...