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There is a simple way to implement waypoint navigation. The algorithm was introduced by Lawrence, Frew, and Pisano back in 2008. You can view the paper here: http://dx.doi.org/10.2514/1.34896.

I have flight tested this algorithm multiple times on a low-resource autopilot embarked on a fixed-wing UAV (see figure below). In this blog post, I want to share my approach to implementing this algorithm. I cannot claim any academic novelty. However, I hope to make this simple and effective algorithm more accessible to other researchers/hobbyists.

In the remainder of this post, I will provide a high-level view of the algorithm. I will also show some flight test results. If the reader wants a more mathematical treatment of the implementation, the reader is referred to the attached PDF.

The algorithm is simple because it uses a single guidance vector field. Vector fields, in general, assign a vector to each point in space. Guidance vector fields, in particular, assign a desired velocity vector to ea

Stereoscopic systems widely used in drone navigation, but this project is using a new approach - variable baseline.

In the related Arxiv.org (PDF) the team showcases three different applications of this system for quadrotor navigation:

• flying through a forest
• flying through an unknown shaped/location static/dynamic gap
• accurate 3D pose detection of an independently moving object

They show that their variable baseline system is accurate and robust in all three scenarios.

For the video capture, the Raspberry Pi-based StereoPi board was used. Additional AI-acceleration hardware (Intel Movidus) is considered as a next step, as well as using a more powerful CM4-based version of the StereoPi (v2).

Here is the brief video of the project:

Hello, people.

I decided to open a new thread to register some progress about this project. I am working on it in my spare time, and I feel excited about it.

This is a very preliminar video -- please disregard the pink view, I was using an infrared camera -- with a normal camera the video is way more clear and interesting. I also need to find better 180º (or better yet, 230º) lens. I am also willing to go full 360 degrees eventually.

So, it is an experimental Virtual Reality controlled drone with some AR features which I will show when I finish implementing them. The plan is to have one or more people walking and controlling the drone as if they were truly inside the physical aircraft. Much like the traditional FPV, but not limited to the video view only, as the crew will be able to interact and walk around freely while they fly.

I have lots of ideas to implement on this experiment. I plan to talk about them while they are implemented.

At first I wanted to show it only after I had a real fl

Renewable drones are planned to expand at a rapid pace as the industry focuses on UAV services, line-of-sight applications, ocean-going ship tracking, inspection or wind turbine inspection, an inspection of offshore platforms and refineries, monitoring of power lines, and solar panels in the energy sector. As one way to alleviate congestion and enhance the air quality in urban areas, passenger drones have been touted. Equipped with thermal cameras, drones make it possible to conduct inspections rapidly and on a scale. On wind farms around the world, drones are changing inspections. Wind turbines are left exposed to the elements as they run - both onshore and offshore. Also, minor damage and wasted energy can cause inefficiencies. By offering rapid and remote coverage of turbines, drones will reduce the time engineers need to spend in precarious positions. The technology is also much cheaper than a manned team, ensuring that wind farms can carry out drone inspections of wind turbines wi

I want to share the first flight of the third development of a fixed wing aircraft for autonomous flight.
This design was made entirely with composite materials and the molds made with 3d printers.
tests resulted in great aerodynamic efficiency and stability and maneuverability
final weight with full payload is 2.6 kg.
for the flight he was ballasted with the final weight for flight.
we estimate endurance of 90 minutes with 10,000 mA and 4S

It has been awhile since I’ve posted anything about recent Centeye hardware. Some of you may remember my past work implementing light weight integrated vision sensors (both stereo and monocular) for “micro” and “nano” drones. These incorporated vision chips I personally designed (and had fabricated in Texas) and allowed combined optical flow, stereo depth, and proximity sensing in just 1.1 grams. Four of these on a Crazyflie were enough to provide omnidirectional obstacle avoidance and tunnel following in all ambient lighting conditions. Their main weakness was that they were time-consuming and expensive to make and adapt to new platforms. Some of you may also remember our ArduEye project, which used our Stonyman vision chip and was our first foray into open hardware. Although that project had a slow start, it did find use in a variety of applications ranging from robotics to eye tracking. I have discussed, privately with many people, rebooting the ArduEye project in some form.

Like man

From the video description:

I wanted to put this video together to share what I've been working on as it relates to PX4 simulation. I've been really impressed with the capabilities of AirSim and I hope this video makes it a little easier to understand. You can learn more about AirSim here: https://github.com/microsoft/AirSim and my GitBook notes can be found here: https://droneblocks.gitbook.io/airsim... To learn more about DroneBlocks please visit: https://www.droneblocks.io Please feel free to leave a comment below if you have any questions and I hope to share more information in the near future. Thanks for watching.

• v4 is super fast to install on most batteries with a tool, and connects to the balance leads.
• The modular board make it possible to reuse BatMon after end of life of a battery. The XT90 leads can be replaced if they are worn, but can practically be reused few times, reducing the cost overhead on each smart battery pack.

Clever research from ETH showing how it uses the drone camera to maintain position while a quadcopter spins to maintain control after one motor fails. 

From DroneDJ:

Researchers at the University of Zurich and the Delft University of Technology have been able to keep a drone flying after a motor fails. The researchers have managed to use onboard cameras to keep the test drones in the air and flying safely.

A team of researchers has come up with a simple yet ingenious way to solve a problem that will usually result in a drone falling to the ground due to a motor failure.

Well, motor failures don’t often happen, but when they do, the drone needs to stay in the air regardless, especially if people are nearby or the drone is being used for a commercial job. Redundancy is important when it comes to drones.

Davide Scaramuzza, head of the Robotics and Perception Group at UZH and of the Rescue Robotics grand challenge at NCCR Robotics, shared:

When one rotor fails, the drone begins

Zion Market Research has published a new report titled “Drone Logistics and Transportation Market By Solution (Shipping, Warehousing, Software, and Infrastructure), By Drone (Passenger, Freight, and Ambulance), and By Sector (Commercial and Military): Global Industry Perspective, Comprehensive Analysis, and Forecast, 2018–2025”. According to the report, the global drone logistics and transportation market was USD 4.56 billion in 2018 and is expected to reach around USD 18.05 billion by 2025, at a CAGR approximately 21.9% between 2019 and 2025.

Unmanned aerial vehicles, also known as drones, are small aircrafts that don’t have a human pilot onboard that can either operated remotely or automated and travel with the help of GPS coordinates. They are made of light material to reduce weight, which enables them to fly at high altitudes. Drones are controlled by a ground cockpit and can easily return to their marked starting position in case of low battery or when the drone loses contact with