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Sailing Auto Pilot - Competition - Ready For Tomorrow 2022

Farnell partners with sailor Alberto Riva to redevelop a Nautical Autopilot image

Alberto Riva is a multi-competition winning skipper who always had a passion for sailing since he was a child.

With the support of many different sponsors, he has sailed on a variety of boats from smaller centreboard boats to 70ft long flying trimarans, on board of which he competed many different regattas.i

He now has an eye on a new dream: the Mini Transat - a 4050 nautical miles solo race on the smallest offshore racing boats at only 6.50m long. A challenge that requires not only competence and resilience, but also a sound mind.

Far from being only a sailing passionate and competitor, indeed, Alberto is also a trained engineer who worked as data analyst and on-board electronics expert for the preparation of other racing boats. With a master in nanotechnologies, he also developed an auto-pilot board during his studies

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The auto-pilot is an element that he defines “his best friend” during sailing, as it allows him to leave the wheel and rest or focus on weather conditions especially on demanding regattas like the Transat, where one-person sailing and no phone/computer or technical support aside from tracking are the main requirements.

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Interface for AutoPilot 

In light of all the characteristics that distinguish this challenge, such as passion, determination, performance, resilience and technology, Farnell decided to partner with Alberto and help him by opening the project up to our open-source design community to redesign his autopilot. As technologies develop further and faster, we are confident that our electronics enthusiasts could highly improve it to achieve higher performances with better cost efficiency.

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Among the improvements Alberto would add, he would certainly focus on changing the current screen (which was an additional cost on the overall system) in favour of taking advantage of new smart phone technologies. Connecting a smart phone to the automatic navigation system could allow to cut a big part of development and budget effort, as it would allow to use the embedded characteristics of modern displays such as waterproofness and mechanical resistance, and make it further flexible and efficient.

Join Alberto in his challenge!

Auto Pilot Components

What do you need for a boat to sail its self? 

The autopilot is made by two parts: The data acquisition and the control part.
Several sensor are connected to the system to perform the vectorial calculation of the wind and gain information about the heading of the boat: IMU compass, wind sensor, boat speed sensor and a rudder sensor.

The calculated variables are used to keep the boat on a particular true wind angle or on a particular course. Two nested PID controllers allow the boat to keep the desired route moving the rudder through a linear actuator.

The first PID calculates the desired rudder angle. The second PID, thanks to the rudder angle sensor feedback, drives the motor of the actuator to the desired rudder angle.

The first controller can be set to follow a particular reference: TWA (True Wind Angle), AWA (Apparent Wind Angle), Internal Gyro Compass (preferred choice), Fixed Rudder Angle (debugging purpose).

 

Ancient mariners would tie the rudder with a rope but this could run them into rocks in their sleep. 
Alberto has used electronics to monitor the wind, position and control it all with an Arduino 

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Components 

Learn more about the components used in this build

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Arduino Max232 Driver Interface 12v-5v DC to DC Converter H-Bridge Motor Drivers Resistors 

Arduino

 Driver Interfaces DC to DC Converters Motor Drivers Resistors

Are you ready for Tomorrow? 

Competition

Global Competition
Winner
 		 Australia and New Zealand
Winner
 

India
Winner
 

 Greater China
(China, Taiwan, Hong Kong)
Closed

 ASEAN
(Singapore, Malaysia, Phillipines, Vietnam, Thailand) + Korea
Winner
 
image image image image image

 

Enter our "Ready for Tomorrow" competition for a chance to win a prize from our prize pool

Multicomp Pro Handheld Oscilloscope - Hand Held Oscilloscope
Multicomp Pro PC USB Oscilloscope - USB Oscilloscope
Multicomp Pro Soldering Station - Soldering Station

Mulitcomp Pro Handheld Multimeter - Multimeter


Details of your answers and contact details can be shared with element14 Avnet Group

 

Parents

  • As I understood there are two purposes in this challenge: the first one is the improvement of the control architecture of the autopilot regarding performance and price, the second one is the improvement of the entire data acquisition instrumentation and the remotion of the display with an Android app.

    The advices really depend on the architecture, so it would have been useful to have some additional information on the bus communication. It is a NMEA2000 bus or it is a serial communication bus like NMEA0183? The image of the instrumentation used is very poor. I didn’t understand if there is a wind vane on the masthead (I supposed yes) and I don’t understand the use of the Wheatstone bridge.

    Anyway, due the presence of the MAX232 device I think there are several serial lines and one central unit (Arduino?). I have three possible solutions to improve the architecture:

    1. Use an ESP32 board like (https://it.farnell.com/dfrobot/dfr0478/mcu-iot-firebeetle-esp32-arduino/dp/3517881?gclid=Cj0KCQjwxtSSBhDYARIsAEn0thR1tDv59YzjDuK_kV4BZsTfwRBufm--mijJbVa-AWRUeiGyLioI8dQaAoDSEALw_wcB&mckv=s_dc|pcrid|579368398304|plid||kword||match||slid||product|3517881|pgrid|123818254960|ptaid|aud-912823420205:pla-339536341562&CMP=KNC-GIT-GEN-SHOPPING-SMEC-01-Mar-2021_Low-Desktop&gross_price=true) or adding an ESP01 module to your Arduino board and implement and MQTT protocol. Then implement an interface on your android with Node-Red. Node-Red is an open source browser-based flow editing and it is easy to understand and use.

    Here there is a good example: https://create.arduino.cc/projecthub/officine/interfacing-arduino-mkr-or-esp-via-mqtt-node-red-101-4833bc.

    If you have a NMEA2000 network consider to follow the example on github.com/ttlappalainen. 

    1. Use a raspberry Pi and Openplotter (https://openplotter.readthedocs.io/en/2.x.x/). Openplotter is an interesting project with a lot of example and features. It is easy to configure and you can connect a lot of devices via USB, I2C, SPI or CAN/NMEA2000.  

    image

    You don’t have to manage all single device but the system export data in the signalK server which is a new communication standard based on JSON format.

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    There are a lot of plugins that you can use like Node-Red or Grafana for the dashboard and Inluxdb (database, see figure below).

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    Finally, you can see directly the monitor or you can see the webpage/dashboard (see figure below).

     imageimageimage

    1. Use Arduino/ESP32 to control the autopilot and the raspberry as central unit. The first solution is more deterministic and fast (ESP32 is dual core) however if you want to add some sensor you have to write code and test, moreover, use Wi-Fi fill performance. The second solution is powerful but I am not sure about its deterministic behaviour, specially if you have to control the pilot with a frequency higher than 2-5 Hz. On my opinion is more reliable to use a power board like Due or Teensy to directly control the pilot and acquire signals from serial lines from wind sensors and heading/GPS. Then, this board must send data to the raspberry which should: log data, expose a human interface for your mobile, perform some additional information like drift or tie and finally manage extra sensors (I2C) and interface (openCPN).

    Beyond the architecture I think that the most challenging problem for the good implementation of an autopilot is the correct estimation of the wind. As mentioned, you can choose the setpoint based on the heading angle or wind angle. If you use the pilot during sailing, obviously, you cannot ignore the wind direction because the risk is sailing against the wind or do some involuntary manoeuvres. The first suggestion is to adding a gyro to the magnetometer and compass (https://it.farnell.com/dfrobot/sen0142/sensore-6dof-fermion-mpu-6050/dp/3769961?gclid=Cj0KCQjwxtSSBhDYARIsAEn0thRg2Y3E7HietmkYoC3oYQp4dcbgECyGZQyc3GJ-FE8pZ1yxu3V8YggaAngJEALw_wcB&mckv=_dc|pcrid|533562556786|plid||kword||match||slid||product|3769961|pgrid|126448169642|ptaid|pla-1385743302654&CMP=KNC-GIT-GEN-SHOPPING-SMART-Development-Tools-Software_10-Jan-22&gross_price=true) to the masthead or directly to raspberry because with this you can correct the error derived from yaw and pitch of the boat. However, the error of the wind vane still remain and it is more challenging to fix (maybe adding some AI). One way you can test if it work fine is to check the TWD before and after the tack, if it remain the same you have a good measurement.

    Further, I suggest adding a bme280 or bme680 to take trace of environmental data. During an ocean sailing it is very useful because the weather is dominated by cyclones and anticyclones and visualize the trend of, for example, pressure could help you to predict rapid wind variation to avoid stressing the controller.

    I think that the real problem of the project isn’t on the human interface but on the tuning of the controller and the damping of the measurement. A simple safe strategy could be using the heading for the feedback and at the same time monitor the wind in order to send alarm and avoid unsafe navigation after this several tests must be carried out to test the pilot in different weather condition and for this reason the key is storing the data.

    On my opinion, my solution is cheap:

    • ESP32 (optional) 11€
    • Raspberry 50-70 €
    • MPU 9250 or similar 20 €
    • BME280 15€

    I think this is a very interesting project and if you want, Alberto, I would be glad to help with data or set-up.

  • in reply to Gcaravello

    Great suggestions. However, having wifi and other wireless connectivity will consume more power. Since, the system is going to be installed on a boat with limited power supply, I think the entire design needs to be calculated for it's power budget along with it's cost.

  • in reply to rsjawale24

    I agree with you however raspberry consume few watt respect to the autopilot control and in addition to this using WiFi is the fastest way to implement an HMI to and Android mobile. another way could be Bluetooth but, on my opinion, it is more complex

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