The conference aims to bring together academia and industries to exchange visions and ideas in the state of the art and practice of Unmanned Aerial Vehicle Technologies and Applications. We invite you to share your scientific findings, newest research projects, as well as industry and line-of-business solutions.
DATE, TIME & VENUE
- Tuesday, 26 May, 2020: from 10:00 to 18:00
- Wednesday, 27 May, 2020: from 10:00 to 17:00
- Adlershof con.vent. Rudower Chaussee 17, 12489 Berlin, Germany.
FEES & RULES
|Developer/Researcher/Academia||Free of charge|
|Exhibitor||Speakers will be charged 400,-€ for up to 30 minute presentation (price excl. VAT)|
|Other||Speakers will be charged 800,-€ for up to 30 minute presentation (price excl. VAT)|
- There is no fee to submit a proposal.
- The duration of most presentations is 15-30 minutes, including time for a question and answer period.
- DRONE Berlin reserves the sole right to accept or reject any proposal received without liability.
- DRONE Berlin does not pay for a speaking fee. Travel related expenses, meals and ccommodations are the responsibility of the speaker.
- If attendees are charged a fee, the speaker shall submit requests prior to the event for review and approval by DRONE Berlin.
Conference language is English.
CHOOSE YOUR METHOD OF SUBMISSION
If you are selected to speak at the event, you will be notified approximately 6-8 weeks prior to event.
INVITE YOUR AUDIENCES
Your presentation is meeting place for your professional connections. As a presenter you might wish to invite audiences and give them complimentary tickets. Our “Invite & Meet” Customer Ticket Package (discounted invite tickets) offers a marketing tool you can use to invite guests to attend your presentation and meet each other without paying admission.
All programs are free to attend by the general admission ticket holder.
The organizer of DRONE Berlin invites proposals for special sessions to be held during the main conference from 26 to 27 May, 2020 in Berlin.
To submit a proposal, please send a summary containing the following information:
- Special session title
- Organizers (complete address, phone, and email)
- Abstract (up to 300 words)
- List of special sub-topics, if any
For submissions or inquiries please email firstname.lastname@example.org.
We will keep updating programs and details in the coming weeks. The information contained herein is subject to change without prior notice, please check back for updates.
Semantic Segmentation of UAV Aerial Videos using Convolutional Neural Networks
UNIFIED AI LAB
Semantic segmentation of complex aerial videos enables a better understanding of scene and context. This enhances the performance of automated video processing techniques like anomaly detection, object detection, event detection and other applications. But, there is a limited study of semantic segmentation in aerial videos due to non-availability of the relevant dataset. To address this, an aerial video dataset is captured using DJI Phantom 3 professional drone and is annotated manually. In addition, the proposed research work investigates the performance of semantic segmentation algorithms for aerial videos implemented using Fully Convolution Networks (FCN) and U-net architectures.
Mission and Path Planning for Drones
BRANDENBURG UNIVERSITY OF TECHNOLOGY
The mission and path planning problem for an inhomogeneous fleet of unmanned aerial vehicles (UAVs) asks for optimal trajectories that together visit a largest possible subsets from a list of desired targets. When selected, each target must be traversed within a certain maximal distance and within a certain time interval. The UAVs differ with respect to their sensor properties, speeds, and operating ranges. The UAVs’ trajectories must avoid „forbidden“ areas. Also the fuel consumption rates during cruise, climb and descend is considered. We formulate the mission and path planning problem for UAVs as mixed-integer nonlinear control problem, and solve it numerically using available software tools for different scenarios with varying numbers of potential targets, fleet sizes, and restricted areas.
Dynamic task allocation in an autonomous mult-uav mission
MASSACHUSETTS INSTITUTE OF TECHNOLOGY (MIT)
A mechanism for dynamically allocating tasks among multiple UAVs operating autonomously during a mission is discussed. Task assignment is adjusted by each UAV dynamically during the mission based on criteria related to the individual UAV's operational status and/or mission parameters. Task allocation is determined independently without group communication between the UAVs actively taking part in the mission and without direct communication to a ground-based controller. A communication UAV pro videos a shared memory space that may be utilized by each UAV in determining its own task allocation.
Enabling BVLOS flights through Cellular Connectivity
Nokia Bell Labs
BVLOS flights enable many exciting new use cases for drones, but require a reliable command and control (C2) link. C2 over cellular networks is an obvious way forward due to the almost ubiquitous coverage. From research conducted in the SESAR DroC2om project, we will show the differences between communication to drones and ground users based on measurements with drones flying in VLL air space, and show that interference mitigation techniques such as interference coordination, beamsteering and hybrid access may well lead to a reliable C2 link even in highly loaded cellular networks.
1000 Payloads/1000 Operations
In the drone industry the most important device for the success of the operation is the payload. As manufacturer, Dronetools has develop few different payloads for a variety applications, from typical visual cameras for rescue or border control to payloads for environmental measurements, or payloads for spry solid or liquid for treatments applications. On the presentation we´ll show the experience gained on the develop of the payloads for our customers and pictures and example of use of those payloads.
Challenges and Techniques in Drone Forensics
Canterbury Christ Chruch Univ.
Due ot the rise in drone-related crimes in recent years, the need for forensic analysis of the captured drones has augmented immensely. This talk presents the challenges and techniques in extraction and identification of important artefacts from the recorded flight data as well as the associated mobile devices using open sources tools and some basic scripts developed to aid the analysis of two popular drone systems - the DJI Phantom 3 Professional and Parrot AR.Drone 2.0.
Air Learning: An AI Research Platform for Algorithm-Hardware Benchmarking of Autonomous Aerial Robots
THE UNIVERSITY OF TEXAS AT AUSTIN
We introduce Air Learning, an AI research platform for benchmarking algorithm-hardware performance and energy efficiency trade-offs. We focus in particular on deep reinforcement learning (RL) interactions in autonomous unmanned aerial vehicles (UAVs). Equipped with a random environment generator, AirLearning exposes a UAV to a diverse set of challenging scenarios. Users can specify a task, train different RL policies and evaluate their performance and energy efficiency on a variety of hardware platforms.
Self-organizing UAV Networks for Providing On-demand LTE Connectivity to First Responders
NEC Laboratories America
The presentation will highlight one of the first system efforts (SkyLiTE) to realize a self-organizing network of UAVs that can be deployed on-demand and un-tethered (to ground stations) to provide multi-cell LTE network connectivity over a wide area. SkyLiTE incorporates a novel, redesign of the LTE core to deploy a stand-alone network of LTE base stations (RAN+EPC on UAVs) in the sky. SkyLiTE can be deployed to supplement existing stationary cellular deployments. More importantly, it can be deployed in a stand-alone manner to provide LTE connectivity in first responder situations.
UAV-Based Situational Awareness System Using Deep Learning
THE UNIVERSITY OF SYDNEY
Situational awareness by Unmanned Aerial Vehicles (UAVs) is important for many applications such as surveillance, search and rescue, and disaster response. we developed the Person-Action-Locator (PAL), a novel UAV-based situational awareness system. The PAL system addresses the first issue by analyzing the video feed onboard the UAV, powered by a supercomputer-on-a-module. Specifically, as a support for human operators, the PAL system relies on Deep Learning models to automatically detect people and recognize their actions in near real-time. To address the third issue, we developed a Pixel2GPS converter that estimates the location of people from the video feed. The result - icons representing detected people labeled by their actions - is visualized on the map interface of the PAL system.
AeroInspekt - Automated Aerial Surveying of Rail Infrastructuree
TU BRAUNSCHWEIG - INSTITUTE OF FLIGHT GUIDANCE
Manual routine inspection of infrastructure is often cost and time intensive due to manual labor and survey related down-time. The presented research project AeroInspekt by HHLA and TU Braunschweig developed and evaluated an approach based on drone photogrammetry to survey crane rails infrastructure in Hamburg's container terminal. The approach aims to build an automated workflow to survey the rails with Millimeter-resolution even during crane operation. Therefore an adaptive mission planner, specialized ground control points and an automated data extraction workflow has been established and tested in operation.
Air-to Air, Air-to-Ground Laser Communications Systems for Drones
Drones are collecting enormous amount of data using smart payloads. There is a need for down-stream large volume of data at high speed from Air-to-Ground and between Air-to-Air in near real time. Small drone operators offered to use LTE, 4G, 5G to transmit collected data. Lasercom is an independent solution, is exceptionally secure as the laser beam is extremely narrow compared to RF signals, it cannot be tapped, jammed or spoofed, free from ITU regulations, low cost per bit, eye safe at short distances. Henceforth, Lasercom solutions will be going to play an important role in bridging this technology gap. Mynaric developing Free Space Optical Communication (FSOC) system to be used on drones of various sizes.
Smart FC(R) - Customized flight controller
When developing a proprietary drone, a well working flight control is key for safe operation. While commercial solutions provide the basic features necessary to fly new drones, a commercial solution tailored to individual drone characteristics is still missing. At TU Berlin, we have developed such an integrated flight control system with a customizable flight controller (Smart FC®). Drone dimensions are collected with a camera system and the information is complemented through an online toolbox. The flight controller is programmed automatically. The presentation will review the logic behind the Smart FC® system and discuss applications and benefits for the drone community.
Swarm Information Gathering with Autonomously Flying UAVs
GERMAN AEROSPACE CENTER (DLR)
In this talk I will introduce a drones swarm system that we developed at the German Aerospace Center (DLR). Our system allows an operator to monitor an area of interest with a swarm of autonomous drones. First, I will present an overview of our developed system. This will be followed by results of a measurement campaign that we carried out within the framework of H2020 HEIMDALL project. In the campaign, we used our system to monitor an area of interest to search for potential wildfire hotspots. I will finalize this talk with an outline of our latest research on the use of deep reinforcement learning methods to monitor a wildfire front with a swarm of drones.
Autonomous Flight in the Wild: Progress and Challenges from Skydio
The technology for intelligent and trustworthy navigation of autonomous UAVs is just reaching the inflection point to provide enormous value across video capture, inspection, mapping, monitoring, and delivery. At Skydio we believe the ability to handle difficult unknown scenarios onboard and in real-time based on visual sensing is the key to making that happen, within a tightly integrated system from pixels to propellers. I will discuss our learnings from shipping a fully autonomous drone, the algorithms that make it work, and challenges beyond.
Mapping multispectral Digital Images using a Cloud Computing software: applications from UAV images
UNIVERSIDAD DE EXTREMADURA
This presentation reports an experience related to the analysis of a vineyard with multispectral photogrammetry technology and UAVs and it demonstrates its great potential to analyze the Normalized Difference Vegetation Index (NDVI), the Near-Infrared Spectroscopy (NIRS) and the Digital Elevation Model (DEM) applied in the agriculture framework to collect information on the vegetative state of the crop, soil and plant moisture, and biomass density maps of. In addition, the collected information is analyzed with the PIX4D Cloud Computing technology software and its advantages over software that work with other data processing are highlighted.
In-flight Wireless Charging for Drones
Global Energy Transmission, Co
One of the key technical obstacles for drone industry adoption is short battery lifetime. It severely limits flight duration for applications including agriculture, delivery, filming, inventory, monitoring and security. Despite alternative power sources (fuel cells, etc.) and other battery industry developments short drone battery lifetime greatly limits drone solutions. Global Energy Transmission (GET) now uniquely enables unlimited drone flight time with its award-winning GET wireless power technology. GET’s turnkey solution enables battery-powered drones to fly forever by safely and quickly recharging while still in flight. Drones simply hover for a short time in one of our large area power hotspots, which can be installed kilometers apart along flight routes. GET will explain their vision of the future of drone industry, and why wireless power charging can totally transform the industry, not just for today’s needs, but also for longer-term future uses including urban air transportation. Visit us at www.getcorp.com
Drone Projects @ Cyber Innovation Hub of German Armed Forces
Cyber Innovation Hub
Bundeswehr Cyber Innovation Hub -the Cyber Innovation Hub of the German Armed Forces is a unit responsible for innovation and technology scouting for the German military. The unit formed in 2017 is operating as an interface between the German Armed Forces and the digital startup ecosystem. It is focusing on disruptive technologies from the field of cyber/it and digital products and services.
DATE & LOCATION
DRONE Berlin, 26.-27.05.2020
Rudower Chaussee 17, 12489 Berlin
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