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Institute for Factory Automation and Production Systems, Friedrich-Alexander-Universität Erlangen-Nürnberg, Egerlandstr. 7-9, 91058 Erlangen, Germany

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2 Papers

Efficient Semantic Mapping in Dynamic Environments

Topics: Tracking and Visual Navigation; Vision for Robotics; Mobile and Egocentric Object Detection and Recognition; Mobile Vision

Authors: Christian Hofmann , Mathias Fichtner , Markus Lieret and Jörg Franke

Affiliation: Institute for Factory Automation and Production Systems, Friedrich-Alexander-Universität Erlangen-Nürnberg, Egerlandstr. 7-9, 91058 Erlangen, Germany

Digital Object Identifier: 10.5220/0010770200003124

Proceedings of VISAPP 2022/VISIGRAPP, ISBN: 978-989-758-555-5

Quick Abstract

Unmanned Aerial Vehicles (UAVs) are required to fulfill more and more complex tasks in indoor environments like inspection, stock-taking or transportation of goods. For these tasks, they need to percept objects and obstacles in the environment, navigate safely in it and sometimes even interact with it. A step towards generating a comprehensive environmental overview for robots are semantic maps. Nevertheless, UAVs have several constraints concerning size, weight and power consumption and thus computational resources. In this paper an efficient object-oriented semantic mapping approach suitable for UAVs and similar constrained robots in dynamic environments is proposed. The approach can be completely executed on a computer suited as onboard computer of an UAV. A map comprising semantic information and dynamic objects is generated and updated with update rate of more than 10 Hz.

Human Detection and Gesture Recognition for the Navigation of Unmanned Aircraft

Topics: Vision for Robotics; Human and Computer Interaction; Mobile Vision

Authors: Markus Lieret , Maximilian Hübner , Christian Hofmann and Jörg Franke

Affiliation: Institute for Factory Automation and Production Systems, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Egerlandstr. 7-9, 91058 Erlangen, Germany

Digital Object Identifier: 10.5220/0010832500003124

Proceedings of VISAPP 2022/VISIGRAPP, ISBN: 978-989-758-555-5

Quick Abstract

Unmanned aircraft (UA) have become increasingly popular for different industrial indoor applications in recent years. Typical applications include the automated stocktaking in high bay warehouses, the automated transport of materials or inspection tasks. Due to limited space in indoor environments and the ongoing production, the UA oftentimes need to operate in less distance to humans compared to outdoor applications. To reduce the risk of danger to persons present in the working area of the UA, it is necessary to enable the UA to perceive and locate persons and to react appropriately to their behaviour. Within this paper, we present an approach to influence the flight mission of autonomous UA using different gestures. Thereby, the UA detects persons within its flight path using an on-board camera and pauses its current flight mission. Subsequently, the body posture of the detected persons is determined so that the persons can provide further flight instructions to the UA via defined gestures. The proposed approach is evaluated by means of simulation and real world flight tests and shows an accuracy of the gesture recognition between 82 and 100 percent, depending on the distance between the persons and the UA.