No abstract

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.

No abstract

Wireless Mesh Networks (WMNs) provide a promising foundation for a flexible and reliable communication infrastructure in industrial environments.Meeting the QoS demands of real-time applications, though, requires the deployment of various advanced mechanisms. Compared to wired networks, applications face higher packet loss rates in wireless networks due to the inherent unreliability of wireless communication. Furthermore, if mobile stations are involved, links that fail due to node movement frequently cause packet losses. In this paper, we present an approach to tolerate those specific losses by locally recovering lost packets and transiently re-routing them over an alternative path. The evaluation in real-world experiments shows that we can completely prevent packet loss without significantly increasing the end-to-end latency. This allows the deployment of WMNs for real-time applications without explicitly considering the increased error-proneness of wireless communication and station mobility.

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...