Discussions

I know this statement will raise the question who is this guy coming and telling us that current day autopilots are all wrong. Well I have been flying RC Planes from the age of 10 and have been using autopilots from the early Ardupilot of 2009 -2010 vintage till the more recent ones from 3DR, DJI, Feiyutech including their cheap clones  over the last 5-6 years. I have been coding from the age of 15 and am now 21 years old.
 
Based on my experience with this wide range of autopilots I have come to the conclusion that hardware of majority of autopilots  are adapted from the world of data based computing made for processing huge chunks of predefined data and giving a appropriate notification or display. In the case of data based computing inputs are got from low response data source like Ethernet/internet or some sensor network, this  data is processed and outputs are either notifications or a display and in a few cases some very slow speed controls. Nothing where high speed control of a dynamic object is involved even on a single axis.
 
Hence  the question : are these processors/hardware  made for controlling a dynamic moving object with freedom across 3 axis’s like a drone??
 
After using all types of available autopilots I realized that the fundamentals of  drone control at its core requires the following steps to be done repeatedly as fast as possible
1. reading  sensor values and conveying them to the controller/processor
2. filtering  these  sensor values
3. pushing the filtered values  into a PID loop
4. transferring control commands to the actuators for immediate action.

This cycle needs to be repeated over and over again the faster the better . This is what determines the stability of the drone the higher the cycle time the higher the stability .So what is needed in the case of drones is a continuous high speed input –output action reaction control system. I realized that drone control is not so much about data crunching as about speed of the control cycle.

If the use of  drones has to grow developers have to be given freedom to code for their applications without compromising this core control cycle. In the case of drones a developers code resulting in a system hang will result in catastrophic outcomes like either crashs or fly aways, both which have been regularly reported in current autopilots. Achieving high control cycle speeds & isolating the flight controls is not possible with the current architecture of sequential processing, hence the future of drones is limited by the architecture of
currently available autopilots.

So unless a new thought process emerges drone use cannot grow exponentially. What is needed is a motherboard that it radically different from anything available today.

I have been working on this for a while now and my first hand experience is that the moment I shifted my focus to achieving higher speed control loops with my self  designed autopilot the level of stability and performance I have been able to get are awesome even in very high costal wind speeds on a small 250 mm racer. I achieved this with the most primitive of micro controller used in the first ardupilot  the  ATMEGA 328. Things got even better when I replaced the MPU 6050. IMU with the MPU 9250.

With my custom made Distributed Parallel Control Computing Bus I have been able to achieve Altitude hold with a total drift  accuracy of less than 1 meter  and a very accurate heading hold as well as GPS navigation on the 250 mm  racer. All I did was to add another ATMEGA 328 in parallel to the first one to add on features.

Thanks to this I am able to completely isolate the core flight control loop from the APP development coding there by the drone is never compromised by faulty APP development coding.

Distributed parallel control computing I have found from my own experience is an architecture that really has the potential to create exponential growth in drone applications. I would be interested to know of any other ways by which others are trying to address this core unique control processing requirements of drones.