Over the last few years, the engineers at the company have invested both their time and sleepless nights in formulating a process for the development of Machine learning algorithms that will satisfy real-time constraints with minimal RAM usage. This is quite a tall task as per default, that would force one to do their development directly in C language. Although that seems like the right choice, the downside is the direct correlation of the debugging time with algorithm complexity.  Such a time could have been rather used in optimizing the algorithm within the MATLAB environment which has excellent tools for the analysis, plotting and debugging. So it was decided to rather learn the Code generation process with the hope that future algorithm could be designed in a similar fashion without the hassle of the compiler-specific run-time issues. The development of this machine learning algorithm would eventually be implemented in a 32bit, 160Mhz speed, 260KB RAM microcontroller.

We are very excited to bring to universities and higher education institutes across Africa (and in some part of Europe), our internship programme. In line with our vision to grow a spirit of hope for talented students who need guidance (and want to work on exciting projects with business value), the objectives of the internship are as follows: Improve the industry-readiness for the selected students. Currently only the following disciplines are supported: Engineering (mechanical, aerospace, electronics, mechatronics), Computer Science. Currently only 3rd-year and above students are eligible. Expose students to professional methods of research and development. Increase the probability of employment through gaining valuable work-experience. Guide students through real-world problem-solving, product engineering and commercialization. Combine flexible hours with working from home. This programme is incentivised through output-based remuneration and student referral. If you

Over the past two years, the research and development team has been developing a method to identify faulty motors on a drone without interrupting a mission (automated or manual). This is of high interest as it will give the pilot more information to ensure the successful recovery of the system in the event of a fault. The team of engineers has developed a Machine learning (using Artificial Neural Networks) framework that superimposes the dynamics on the controls in order to detect and locate a fault in a rotor without compromising the mission. The graph above shows simulate a rotor fault once the drone reaches 9 m/s and the fault identification system (FIS) detects a fault 1-second later. Once the other rotors are analyzed, the Rotor1 is identified as having a fault and this information is sent back to the pilot. It's important to know that even though a major fault has occurred, the drone a capable of flying for some time until instability grows and the drone becomes unc

The race towards bringing robotic flying things hasn't slowed down. The effort to reduce the art of electronics and power consumption to a minimal size has often not shown the commercial uptake it deserves. At least from the skills-basis standpoint. It takes a pretty special bunch of individuals to be able to work in a world of the minuscule. The question I guess is more from the intent of the technology. Do you remember the Kodak camera that you could find at any tourist store? At the time, it was brilliant technology with a commercial uptake, but not sustainable for the needs of the future tourist. That technology had to die and die hard. On the other hand, there's aluminium/cast iron pot in the dusty streets of some West African countries, is still made in the same way 30+ years after that technology was conceived. So what makes technology have a staying factor? In the case of microrobots and any new technologies that are on the horizon (like our interest in 3dpr

The impact (good and bad) of drones in society is no longer in question. But what will it take for drones to impact a traditionally outdated, low-profit-margin civil works industry through the use of technology? The solution lies in a low-cost approach. One could say it all started when a bunch of scientists realized they could do a far better job in measuring objects accurately and at a distance rather then an individual putting himself in harm's way and using expensive/primitive equipment for the same task. We're talking about photogrammetry. In a nutshell (or should I say according to Wikipedia), Photogrammetry is the science of making measurements from photographs, especially for recovering the exact positions of surface points. In more simplistic terms, provided you have some form of frame of reference (like a ruler) you can determine the physical properties of objects and their exact location to the accuracy of the remote sensing equipment used (a 4K-size imag