CILLITEC UAV-DRONE

CILLITEC UAV-DRONE

lunedì 17 novembre 2014

DJI T600 Inspire - Hobbyking

DJI T600 Inspire - Hobbyking

 
http://www.hobbyking.com/hobbyking/store/__75615___PRE_ORDER_DJI_T6...



This DJI mutirotor is going to flood the market and with a price tag of $2,899.00 will hopefully keep it out of the beginners hands.







Features:

• Completely READY-TO-FLY

• Innovative transforming design for 360° aerial photography / video

• Leading edge camera for 4K video & 12 megapixel photos

• Modular camera gimbal design for easy transportation & upgradability

• 720p HD Live video output

• Support dual transmission system – photographer & Flyer can control the gimbal & model separately (A extra transmitter is required)

• Optical Flow technology combined with sonic waves rise indoor flying stability to a new level

• Intelligent battery with advanced algorithms – It can calculate the distance of your Inspire 1 from you and keep tracking your battery status, so you can manage the flight time better

• Specially design transmitter to fit FPV needs - Dedicated buttons for photo and video capture, a gimbal control dial, an integrated rechargeable battery, HDMI and USB port allowing you to connect mobile devices or compatible screens.

• 1-click take-off & landing

• Return-to-Home function

• Smartphone controllable

Specification:

DJI Inspire

Weight (Incl. Battery): 2935g

Hovering Accuracy (GPS mode): 0.5m(Vertical), 2.5m (Horizontal)

Max Angular Velocity: 300°/s(Pitch), 150°/s (Yaw)

Max Tilt Angle: 35°

Max Ascent Speed: 5m/s

Max Descent Speed: 4m/s

Max Speed: 22m/s (ATTI mode, no wind)

Max Flight Altitude: 4500m

Max Wind Speed Resistance: 10m/s

Max Flight Time: Appro. 18 minutes

Motor Model: DJI 3510

Propeller Model: DJI 1345

Indoor Hovering: Enabled(Default)

Diagonal Distance: 559 to 581mm

Dimensions: 438x451x301mm

Gimbal

Model: ZENMUSE X3

Output Power (with camera): 9W(Static), 11W(In motion)

Operating Current: 750mA(Static), 900mA(In motion)

Angular Vibration Range: ±0.03°

Mounting: Detachable

Controllable Range: -90° to +30°(Pitch), ±320°(Pan)

Mechanical Range: -125° to +45°(Pitch), ±330°(Pan)

Max Controllable Speed: 120°/s(Pitch), 180°/s(Pan)

Camera

Model: FC350

Resolution: 12.0MP

FOV (Field of View): 94°

CMOS: Sony EXMOR 1/2.3”

Lens:

f/2.8 (20mm equivalent)
9 Elements in 9 groups


Aspherical lens element

Anti-distortion filter

UV filter

Still Photography Modes:

Single shoot

Burst shooting (BURST: 3/5/7 frames, AEB: 3 or 5 bracketed frames at 0.7EV Bias)

Time lapse

HD Video Recording Modes:

UHD (4K): 4096x2160p24/25, 3840x2160p24/25/30

FHD: 1920x1080p24/25/30/48/50/60

HD: 1280x720p24/25/30/48/50/60

Max Bitrate of Video Storage: 60Mbps

Supported File Formats: FAT32/exFAT

Photo: JPEG, DNG

Video: MP4/MOV (MPEG-4 AVC/H.264)

Supported SD Card Types:

SD/SDHC/SDXC Micro SD

Max capacity: 64GB, Class 10 or above

Transmitter

Operating Frequency:

5.728GHz~5.850 GHz (Transmitter to Transmitter)

2.400GHz~2.483GHz (Transmitter to radio)

EIRP: 13dBm@5.8G, 20dBm@2.4G

Video Output Port: USB, HDMI

Dual User Capability: Host-and-Slave

Output Power: 9W

Battery: 6000mAh LiPo 2S

Battery

Capacity: 4500mAh

Voltage: 22.2V / 6cell

Energy: 99.9Wh

Net Weight: 570g

Vision Positioning

Velocity Range: Below 8m/s (2m above ground)

Altitude Range: 5cm-500cm

Operating Environment: Brightly lit (lux >15) patterned surfaces

Operating Range: 0-250cm

Included:

Inspire 1 Quadcopter

Transmitter

ZENMUSE X3 Gimbal and Camera

Charger

Smartphone Holder

4 x Spare Props

$2,899.00




FONTE:DJI T600 Inspire - Hobbyking - DIY Drones

domenica 9 novembre 2014

RPAS Logger Plus now supports exports and syncing with RL Enterprise suite

RPAS Logger Plus now supports exports and syncing with RL Enterprise suite

 




The 2nd app - RPAS Logger Plus - in our RPAS Logger Enterprise suite now enables you to export your logs to create reports as you wish. It is also ready to sync your data with the RPAS Logger Enterprise website. The RPAS Logger Plus app is US$9.99 and the RPAS Logger Lite is Free.

We have developed a suite of mobile and cloud / desktop applications on Android, iOS app and RPAS / sUAS / UAV / Drone Job Management website that integrates with your mobile devices called RPAS Logger (Remotely Piloted Aircraft System = RPAS )

Our iOS app is submitted to Apple and will be available next week. Once the iOS app is available we will officially launch the Enterprise website which is a breakthrough in managing all potential government compliance issues. It is designed to streamline your official Australian CASA application and built according to the latest ICAO requirement which is the standard that the FAA and most Civil Aviation Authorities world wide are aligning their drone laws too.

RPAS Logger EnterpriseThis is the flagship version of RPAS Logger. Unlike the Lite and Pro version, RPAS Logger Enterprise is a cloud-based solution. All Data is kept in the web application and your mobile devices will now become access points that you will be able to use on and off line to collect and log data. You can use the Android / iOS apps when you don't have internet access and sync it up when you connect again. 

The apps include a bar code scanning feature for battery / maintenance management and our latest (most requested feature) allows you to use your GPS location on your mobile device to show you the nearest airport / helipad etc to your current location which will help in completing your Risk Assessment for each job or flight. www.rpaslogger.com 

It is oriented towards a commercial operation or hobby clubs. It will allow you to create jobs for customers, assign equipment and personnel to different jobs, manage area approvals and risk assessments, manage maintenance requirements and inventory.

Modules include:
Basic Module – everything required to create jobs, manage airframes, batteries and role equipment usage, manage pilots (including type endorsements and certifications) and produce comprehensive reports.

  • Maintenance Module – Keep maintenance logs for all equipment and manage your inventory - including shelf life and minimum quantity reporting.
  • UOC Manuals – online management of your flight, operations and maintenance manuals. Easily update your entire documentation suite with any changes that you make to your fleet, role equipment or operational parameters.
We will appreciate any feedback or request for new features. Rest assured, we have a long list of upcoming features but use your comments to help prioritise our updates. 






fonte:RPAS Logger Plus now supports exports and syncing with RL Enterprise suite - DIY Drones

Neruromorphic chip "learns" how to fly



Neruromorphic chip "learns" how to fly

 
From Technology Review:

There isn’t much space between your ears, but what’s in there can do many things that a computer of the same size never could. Your brain is also vastly more energy efficient at interpreting the world visually or understanding speech than any computer system.

That’s why academic and corporate labs have been experimenting with “neuromorphic” chips modeled on features seen in brains. These chips have networks of “neurons” that communicate in spikes of electricity (see “Thinking in Silicon”). They can be significantly more energy-efficient than conventional chips, and some can even automatically reprogram themselves to learn new skills.

Now a neuromorphic chip has been untethered from the lab bench, and tested in a tiny drone aircraft that weighs less than 100 grams.

In the experiment, the prototype chip, with 576 silicon neurons, took in data from the aircraft’s optical, ultrasound, and infrared sensors as it flew between three different rooms.

The first time the drone was flown into each room, the unique pattern of incoming sensor data from the walls, furniture, and other objects caused a pattern of electrical activity in the neurons that the chip had never experienced before. That triggered it to report that it was in a new space, and also caused the ways its neurons connected to one another to change, in a crude mimic of learning in a real brain. Those changes meant that next time the craft entered the same room, it recognized it and signaled as such.

The chip involved is far from ready for practical deployment, but the test offers empirical support for the ideas that have motivated research into neuromorphic chips, says Narayan Srinivasa, who leads HRL’s Center for Neural and Emergent Systems. “This shows it is possible to do learning literally on the fly, while under very strict size, weight, and power constraints,” he says.

The drone, custom built for the test by drone-maker company Aerovironment, based in Monrovia, California, is six inches square, 1.5 inches high, and weighs only 93 grams, including the battery. HRL’s chip made up just 18 grams of the craft’s weight, and used only 50 milliwatts of power. That wouldn’t be nearly enough for a conventional computer to run software that could learn to recognize rooms, says Srinivasa.

The flight test was a challenge set by the Pentagon research agency DARPA as part of a project under which it has funded HRL, IBM, and others to work on neuromorphic chips. One motivation is the hope that neuromorphic chips might make it possible for military drones to make sense of video and sensor data for themselves, instead of always having to beam it down to earth for analysis by computers or humans.


Prototypes made under DARPA’s program—like HRL’s—have delivered promising results, but much work remains before such technology can perform useful work, says Vishal Saxena, an assistant professor working on neuromorphic chips at Boise State University. “The biggest challenge is identifying what the applications will be and developing robust algorithms,” he says.

Researchers also face a chicken-and-egg scenario, with chips being developed without much idea of what algorithms they will run and algorithms being written without a firm idea of what chip designs will become established. At the same time, neuroscientists are still discovering new things about how networks of real brain cells work on information. “There’s a lot of work to be done collectively between circuit and algorithm experts and the neuroscience community,” says Saxena.


fonte:Neruromorphic chip "learns" how to fly - DIY Drones

NIXIE - Wrist Wearable Quad - Intel Make it Wearable $500,000 Contest Winner - DIY Drones





NIXIE - Wrist Wearable Quad - Intel Make it Wearable $500,000 Contest Winner



From Wired, "Called Nixie, this diminutive drone weighs less than a tenth of a pound, but can capture HD images and sync with a smartphone"....In development phase, very nice concept.




fonte:NIXIE - Wrist Wearable Quad - Intel Make it Wearable $500,000 Contest Winner - DIY Drones