3D Printing and Assembling my Robot

 Finally I have enough parts printed to start to assemble my final robot.

Some parts require supporting during the 3D printing process. I have an IDEX printer (Independent Dual EXtruder). This means it has 2 independent tool heads/hot-ends. They can each print a different material. So here I have printed my main part in PLA+, but used PETG for the support material. These different plastics do not stick together very strongly, so I can completely eliminate the vertical separation normally required to make supports removable. Above you can see the indented rectangles and the arch (this part was printed the other way up to how it is shown in the photo. The PLA+ is totally supported in these areas, and the PETG just snaps cleanly off (you can see the small PETG supporting parts behind on the desk).

Around 3 weeks to the competition and I have so much to do! I am away for a week around Easter too, so I have to turn this pile of parts into a working robot this week.

It isn't all advanced digital design and manufacturing. I cut these 'washers' out of plastic milk cartons as the polythene these are made of is really low friction. I put one of these between every pivot joint in the grabber so that the rougher surfaces of the 3D prints move smoothly over each other.

CAD Model Completed

After several late nights working on my CAD model I think I have everything done.

Learning from past mistakes, I included a sketch of the maximum allowed robot size. I also used this to label which motor sockets on the Motor2040 board each of my wheels is connected to, so that I reassemble it correctly when I disassemble my test chassis and rebuild it with the 3D printed parts from this new design. I reused the Pi 5 case design, but reprinted it in better quality in ABS. I added mounting space for a USB-C battery pack which after testing I was happy to confirm is capable of powering the Raspberry Pi 5 with no issue. The twin cell Li-Ion battery pack between the wheels powers the motors (via a 6V UBEC) so they get a constant voltage supply whatever the level of charge of the battery. Using separate batteries also ensures the motors don't cause brown outs for the Pi power supply when the going gets tough.

The whole CAD design is highly modular. This enables each part to be printed separately, reducing the time lost if a print fails or a part needs modifying and reprinting. It also allowed me to get parts printing while I was still working on the rest of the model, saving valuable time.

I really need to get working on my own robot!

Just one month to go until competition day, and I have not started building my own robot yet! Panic has started to set in and I have done some initial work on the CAD for a small chassis to hold the motors and a battery. Based on the design of my small tracked robot, but needing 4 motors instead of 2. I have a design which uses commercial camcorder batteries still commonly used for LED video panel lights. So they are easy to swap out and drop onto a charger.

I spent more time than I probably should on designing a model of the mechanum wheels. But now I have them to add to my common robotics parts CAD model library. I will share them on GrabCAD when I have time to think about things after the competition, so that other members of the robotics community can use them in their own CAD models. I'll do the same with the battery model. I have learned it really pays to model every component and put in all the machine screws and hex nuts in the CAD assemblies. This allows interference detection to be calculated and avoids costly mistakes which require re-printing parts when you discover a servo collides with a nut of some such problem when you try to assemble your design for real.

Working on Attachments with my Young Persons Team

Since my holiday coding, all my Pi Wars time has again been spent mentoring my young person's team. Together we designed a barrel grabber to go on the front of their robot, and started 3D printing the parts for their proper robot. By the time we get to competition day, I will have built 4 robots in total! 2 test platforms and 2 actual competition robots. I am teaching my young persons CAD using SOLIDWORKS. We based the grabber off designs we saw when searching for robot claws on eBay and other direct from China tech selling websites. This is what we came up with.

But I have a cunning plan. Having 3D printed all the parts to fit onto their robot chassis, I am going to design the front of my own robot to have exactly the same mounting points. So I can print a second grabber, camera mount and sensor mounting block and put them onto my own robot. Hopefully this will not over balance my much smaller robot. I plan to put my battery on the back to act as a counter balance for the grabber.

Finally some significant progress with my code

On our family holiday to Dorset where we have gone to hunt for fossils on the Jurassic Coast most years since our children were born. By coincidence I find myself working on my robot in the same holiday let conservatory where I worked on my first ever Pi Wars robot back in 2019.

My first objective is to master rotary encoders in MicroPython. It took me a while to get my head around the examples provided for the Motor2040 board by Pimoroni. One example shows how to control velocity of a motor using PID control to adjust the measured velocity from the encoder to reach a desired target velocity. Another example shows how all four motors can be controlled, but this uses an array of motors, an array of encoder classes and an array of PID controllers. It all gets rather complicated and hard to follow. So I refactored these examples to create a PID controlled encoder+motor class. This massively simplifies the code once the constructor has been passed all the complicated parameters needed to assign an available PIO and state machine. The magic happens inside this class, but all you need to do in your program is call the setVelocity method and the PID controller adjusts the PWM duty cycle of the motor driver to get the motor rotating at that velocity by using the encoder in a feedback loop. Velocity control is great because now all motors can easily be set to run at the same speed regardless of small mechanical differences between them and the load due to robot mass or forces due to driving up or down a slope. Meanwhile the code is kept really simple. 

There is another advantage that comes from using PID control, in that you set a target velocity and the PID controller takes the motor to that velocity in a progressive way. So there is some built in dampening which smooths out sudden changes in requested velocity from the driver. This protects the motor gear boxes from excessive strain which can otherwise strip the teeth from cogs in the gearboxes. If you suddenly slam the power joystick from full power forwards to full power reverse, the PID controller starts to adjust the motor power to comply, but does not immediately give the motor full reverse power. It backs off the power a little, measures the effect on the velocity by reading the encoders and re-adjusts accordingly. The driving is still really responsive, but the motors do not break under the strain.

On to the second objective: mechanum driving. I was disappointed to find that the examples for the Motor2040 just set motor speeds to drift left or right, or move forwards or backwards. No omnidirectional drifting. So I looked for information on the internet and eventually found this excellent article with code examples (in C). I managed to reimplement the equations in MicroPython, finding some bugs in their example which had me scratching my head for a few days until I got it all working. Some of my problems where due to me mixing up my motors, and some due to a copy and paste error in the article where they use the wrong variable to adjust for turn input. Now I could move my robot in any direction using one joystick on my controller, while rotating the robot on the spot using the left-right channel from the other joystick. I think this ability to move in 2 dimensions while independently rotating to face in another direction will be really handy in Pi-Noon!

The final piece of the puzzle was to measure the robot heading, so that I could implement field oriented driving. This is where the robot moves in directions relative to the driver position/arena, regardless of which direction it is actually facing. To put it another way, up on the joystick moves the robot up the arena (away from you) and down moves it back towards you. You can spin the robot around to face in any direction and it still moves away/towards you when you push up or down on the joystick. The magic of mechanum wheels in conjunction with matching wheel velocities due to the velocity controlled encoder motor driving, allowing the robot to move in any direction while pointing in any unrelated direction. The robot just needs to be able to measure it's heading, which requires an IMU. Luckily I had been learning how to use the BNO01 IMU chips on my other small robot project (see my earlier blog entry for Piwars 2024). This IMU chip has on-board sensor fusion, where it combines the 3 axis compass, 3 axis accelerometer and 3 axis gyro readings to calculate a 3 dimensional orientation vector for the robot. Using this you can determine which direction the robot is facing at any point in time, and subtract that angle from the direction the mechanum drive equations are being given to move the robot. This provides field oriented driving, which should be very useful in several of the challenges.

A New Idea to Rescue My Pi Wars Entry

So I need a new idea for my Pi Wars robot. Something small that will be quick to build. I am a big fan of small robots, although it can be challenging to fit everything in the limited space. For me the value of Pi Wars is that it pushes me to learn and advance. I've never really enjoyed the competitive aspect of things, but I really enjoy pushing myself to improve. So I started thinking about building on the ideas I have been working on using a Raspberry Pi communicating to a MicroPython board with the Pimoroni Yukon, but shrinking things down a little. I have wanted to build a robot with Mechanum wheels for a while now. Mechanum wheels have little rollers mounted at a 45 degree angle all around them, and by driving them in different directions it is possible to make a robot move in any direction without turning the body of the robot to face in that direction. I had all the parts I needed in my 'things I bought in Pimoroni sales but have not had time to use yet' boxes. So I swapped the Yukon board for the smaller Motor2040 board which supports 4 independently controllable encoder motors. Encoder motors are another thing on the long list of topics I have wanted to explore but hadn't found the time yet. So I laser cut a pair of acrylic plates with mounting holes for motors, a Raspberry Pi and a Pimoroni Motor2040 board. I already had some motor mounting brackets I had 3D printed on the Makespace resin printer. 

I have a robot! Albeit a test chassis to develop some code on rather than a final Pi Wars entry. I had been designing a case for the new Raspberry Pi 5, so I just mounted that on the chassis. Another step into new learning as the power requirements for the Pi 5 for mobile robotics raise more problems I wanted to solve. The Raspberry Pi 5 also requires running the Bookworm version of Raspberry Pi OS, which means python libraries not included in the apt packaging system can only be installed into a virtual environment. So this would push me to solve the problems of configuring my robot code to run on boot inside a virtual environment. So I will be learning a lot! Now I just need to find some time to work on the code.

Mentoring a Young Persons Team

Mentoring young persons in PiWars has by far been the most rewarding aspect of the competition over the past 5 years. This year is the 7th young persons team I have mentored through the competition. They have pretty much taken up all my time for robotics during this competition so far, hence the lack of progress and updates on my own robot. Time is always very limited with young persons teams. In the past I have always mentored through running after school robotics clubs in local schools. School safe guarding rules generally mean I only get a hour a week with the teams, and have no way to communicate with them outside of these club sessions. This really restricts what I can do with them. I literally get around 20 hours with them over the entire span of the competition, to help them design, build and code a robot. The exception to this has been the monthly Robot Club run by Brian Corteil at Cambridge Makespace, where I have managed to arrange with the parents of some of the children in my teams to bring their children along and give us some more precious time to work on their robots.

This year is a little different as I was unable to get an after school club organised due to staff leaving and schools closing/merging where I had previously made contacts with staff. But then my daughter entered with a school friend giving me a team to mentor who I could work with outside of school. This has made a huge difference both in terms of what we can do, and in how much of my time they have taken up!

Here they are at Makespace where we went to the Robot Club and built this robot in a day!

It was based on the guts of a robot from last year (my daughter was also on that team). We designed and laser cut a base plate with holes to mount all the electronics and batteries, then mounted everything with machine screws. This is just a working development platform to give them something to start working on the code. We looked at my collection of sensor electronics, and they decided to start with a camera as they plan to try and tackle some of the challenges autonomously. This brings me to the second huge benefit of mentoring young people. They teach you so much! I have never done any image recognition before. I always wanted to explore this area, but never found the time until now. Suddenly I am up to my neck in their Open CV code, trying to understand it, help them debug it and advising them on approaches to problem solving. They have some great ideas, slicing images into vertical strips, calculating average brightness to determine where in the frame the line is for the line following for the Lava Palava challenge. Detecting barrels by colour, and recognising Zombies. Even if I never get the time to work on my own robot for this competition, they have pushed my knowledge far into new areas. It has been great!