MAVLink or Micro Air Vehicle Link is a protocol for communicating with small unmanned vehicle. It is designed as a header-only message marshaling library. MAVLink was first released early 2009[1] by Lorenz Meier under LGPL license. It is used mostly for communication between a Ground Control Station (GCS) and Unmanned vehicles, and in the inter-communication of the subsystem of the vehicle. It can be used to transmit the orientation of the vehicle, its GPS location and speed. In version 1.0 the packet structure is the following: To ensure message integrity a CRC is calculated to every message into the last two bytes. Another function of the CRC field is to ensure the sender and receiver both agree in the message that is being transferred. It is computed using an ITU X.25/SAE AS-4 hash of the bytes in the packet, excluding the Start-of-Frame indicator (so 6+n+1 bytes are evaluated, the extra +1 is the seed value). Additionally a seed value is appended to the end of the data when computing the CRC.

The seed is generated with every new message set of the protocol, and it is hashed in a similar way as the packets from each message specifications. Systems using the MAVLink protocol can use a precomputed array to this purpose. The CRC algorithm of MAVLink has been implemented in many languages, like Python[4] and Java. The payload from the packets described above are MAVLink messages. Every message is identifiable by the ID field on the packet, and the payload contains the data from the message. An XML document in the MAVlink source[7] has the definition of the data stored in this payload. Below is the message with ID 24 extracted from the XML[8] document. > > > > > > > > > > > Note: The XML document describes the logical ordering of the fields for the protocol. The actual wire format (and typical in-memory representation) has the fields reordered[9] to reduce Data structure alignment issues. This can be a source of confusion when reading the code generated from the message definitions.

MAVLink is used as the communication protocol in many projects, which may mean there is some compatibility between them. An article explaining MAVLink can be has been written.[10] Some projects known to use MAVLink are:parrot ar drone torinoWhether they're causing concern amongst Brits or crashing into internationally-renowned landmarks, drones never seem far from the news nowadays. parrot ar drone bereikBut, most importantly, the flying machines sometimes known as quadcopters are pretty much the best new tech toy you can buy, endlessly fun and friend-impressing in equal measure.parrot ar drone aucklandIf you are interested in these high-tech flying machines and have a park nearby – or an enviable slice of garden where you can get your full drone on – but don't know where to start, then read on, as we've have collected our favourites to cater for every high flyer.parrot ar drone perdu

Best on a budget: Revell RayvoreDrone flying can be an expensive past-time, but it doesn't have to be. There are absolutely tiny quadcopters, such as the Nano Hex, which start at just £39.99. These micro drones are great stocking fillers and are fun for a while, but due to their lightweight bodies can be extremely unstable, fast, and difficult to control. ar drone 2 macgyver modThey can be mastered, but this takes time and patience.parrot ar drone synchronizedSo that's why we'd recommend going with a slightly larger drone to begin with, such as this Revell Rayvore. Revell is well known for making drone kits, but this little fella comes pre-made and ready to fly.The biggest selling point is its indestructibility – crash it into the cold, hard pavement, fences or trees, even stand on it and the drone will endure the torture and come back for more.

It also has a 50-metre range and four levels of sensitivity to suit beginners and satisfy experts as you get better at it.It's packed in with a standalone controller that packs a 'flip' button also lets you perform simple mid-air tricks. The Rayvore doesn't include a camera – for that, you need to stump up for Revell's X-Spy, which comes in at £99.99.Why's it fly? Durable, kid-friendly and affordableFlight time:10 minutesExpect to pay: £59.99Best for enthusiasts: Parrot BebopThe Bebop Drone is a lightweight flyer from the French wireless firm Parrot, who started the mass-market quadcopter craze back in 2010 with its foam-covered AR Drone. Despite this new device's feather-like weight, though, the BeBop is also incredibly robust, with an ABS-reinforced structure.Where the BeBop drone demands a higher price is in the numerous sensors and tech-laden additions that are included, such as a three-axis accelerometer, gyroscope, magnetometer, one ultrasound sensor with an eight-metre reach, one pressure sensor and a vertical camera to track the speed.

All of these are analysed automatically to ensure a smooth flight.There are also several modes that aim to keep your drone safe, including an 'Emergency' mode, which makes it land immediately, and a 'Return Home' mode, which uses GPS to bring the quadcopter back to where it took off. They're incredibly useful systems that should stop your flying sessions from ending in early tears, but overall we found it both stable and fast.The Bebop is controlled from a smartphone or tablet application, for proper 'modern plaything' points. To ensure a constant and reliable connection the drone packs two dual-band Wi-Fi antennas, generating its own Wi-Fi 802.11 network, and we never had a problem syncing during our testing. However, if you want to go 'fully pro', you can pair it with the intelligent but thankfully optional £340 'Skycontroller' remote and make a sky-owning system out of it.We believe that in the future, exertion activities will become a new experience, involving interactions with autonomous embodied systems.

Our vision is Joggobot, an autonomous flying quadcopter that exemplifies our thinking about the combination of robotics and physical exercise. We use Joggobot to ask the question how (and if) robots should support us when exercising. As such, Joggobot helps us to understand the interactions between a person and a robot. Our Joggobot is able to track the position of the jogger via an built-in camera and tag detection software. This software turns the previously human-controlled quadcopter into an autonomous flying robot that reacts to the jogger’s actions. We ask questions such as “Should the robot be a pacemaker for the jogger? If so, can this be motivating? Or should the Joggobot be more like a dog, reacting to the jogger like a pet companion? How does this affect the interaction, and in particular, the exercise experience for the jogger? Will joggers run faster or longer because of the robot? And, maybe more importantly, will the jog be more engaging?” We believe robots have been so far mainly investigated from a perspective where they do tasks for us we do not want to do: vacuuming floors, going into war zones, and cleaning up nuclear power plants.

With Joggobot, we want to propose the idea of robots as companions for physical activity. We believe this is a promising approach, as both robots and exercise are embodied, by which we mean they are both heavily body-focused. We think that this match in body-focus can lead to more engaging experiences. For example, compare Joggobot to running with one of the many mobile phone apps that support joggers. Such an app does not know about the shape and size of the phone (its “body”), nor does the shape and size of the mobile phone knows (or does) anything about the app or the exercise. Therefore the app is not very body-focused or embodied. Jogging on the other hand is all about the body. And so is Joggobot: it’s a physical device that acts and reacts to its environment and the jogger. Both the Joggobot and the jogger are affected by environmental conditions such as wind. Both’s performance is affected by rain. Both get “tired” (Joggobot’s speed diminishes with low battery) and with both you can hear if they invest physical effort: the jogger puffs, the Joggobot whirrs.

We believe the match in focus on the body can facilitate more engaging experiences, for example joggers might “relate” more to Joggobot because it has a body, they might even develop empathy because both have a body-focused experience. This is important, as we know from sports research that social factors are key when it comes to exercising. We hope our project will enhance our understanding of why we play (and hence why we jog and therefore why we do not jog enough), further the experience of jogging and promote the consideration of robots supporting exertion activities. In the Exertion Games Lab, we investigate the intersection between technology, the body and play, we call this coming together Exertion Games. Joggobot is a form of an exertion game, as jogging is play (we are not jogging to get from A to B, but for the experience of jogging), and the Joggobot represents technology that is part of that experience. Joggobot as well as all of our other exertion games are inspirational pieces to inspire industry of what the future can and should be like in 10 years time.

Joggobot by Eberhard Gräther and Florian ‘Floyd’ Mueller, with help from Wouter Walmink, Chad Toprak, Josh Platt, Conor O’Kane, Jennifer Lade, Jonathan Duckworth, Wendy Ju and Wolfgang Gräther. Video by Eric Dittloff. Graether, E., Mueller, F. 2012. Joggobot: A Flying Companion as Flying Companion. Mueller, F., Wilde, D., Toprak, C., Graether, E., Berthouze, N. 2012. Future User Research for Exertion Games. Workshop User Research in Games. Joggobot video high quality (.mp4) Daily Mail UK: Jog human The robot companion flies just ahead runners track SBS (World News Australia): Jogging robot sets the pace I Programmer: You’re never alone with a Joggobot Quadrotor New Scientist: Go for a jog with a helicopter drone The Age: Flying robot set to spur on flying feet (incl. video) Digital trends: Meet Joggobot, the flying robot that sets your jogging pace Krone: Salzburger Student erfindet fliegenden Jogging-Trainer