(Please note that this tutorial is work in progress)
We appreciate your interest in programming intelligent machines. Here we show you what kind of materials, resources and know-how the working group Smart Machines has to offer. In addition, we are always available for questions and joint projects.
Our idea was to use soft- and hardware for gesture recognition to remotely control drones, mobile robots and robotic arms to intelligently support workflows. A very elegant and easy-to-use method to achieve this is the Tactigon board by Next Industries. It is a very small, easily programmable Arduino based board equipped with a gyroscope, an accelerometer and many other sensors to allow the detection of gestures, and it also comes with enough computing power to interpret them and make them useful.
The advantage of this approach is that the user can control machines intuitively through easily understandable and learnable gestures while retaining a free mind to focus on the actual problem they are working on, not on operating their equipment. And because the Tactigon uses Bluetooth, there are no wires to trip over, either.
In this tutorial we provide you with
references to basic information to get you started
example code and videos
the full API documentation of the Tactigon
game breaking issues that we’ve run into, and possible solutions
For advanced users who have already programmed an Arduino board, we have further information, for example on
the technical implementation of gesture recognition
how to tell the robot where it is, so it can accurately navigate
the man-machine interface concept
To develop applications using the Tactigon, the working group Smart Machines has purchased the drone Crazyflie 2.0 among others. You can find all our information on the Crazyflie, including sample code for use with the Tactigon, on this page.
An important note to conclude: All members of the HS-KL can borrow the resources of the working group at any time; for use in lessons and tutorials, or even for a graduation thesis.
Before you start, you’ll need a system running Windows (tested on 7 and 10, make sure to install the latest windows updates). The Tactigon is not yet compatible with Mac, Linux or other systems (as of September 2018). Additionally, you’ll need a USB-A to micro-USB cable to upload your sketches to the board.
Please note: The Tactigon uses Bluetooth Low Energy (BLE) for wireless communication. Make sure that any other devices you want it to communicate with also support BLE.
The Tactigon is based on the Arduino platform, so for everything to run smoothly, it is recommended that you use the official Arduino IDE for development. You can find it here.
After downloading and installing the IDE, follow this guide to prepare it for the Tactigon.
The full documentation of the Tactigon can be found here and here.
Please note: All code for the Tactigon must be written in C.
Here is a list of topics that will be discussed in the near future:
Bluetooth Low Energy
Follow this tutorial on how to set up BLE on the Tactigon. Please note that there are code samples at the very end of the linked page which the text refers to.
Points to consider:
The role of Tactigon can be CENTRAL or PERIPHERAL, depending on the direction in which the connection should be established. See bleManager.InitRole(TACTIGON_BLE_CENTRAL); in the tutorial code.
BLE is not a mandatory part of Bluetooth, check for compatibility; compliant hardware
UART, BLE to COM, USB HID
serial monitor in Arduino IDE
Sensor values, reading out values
For a list of all classes supported by the tactigon, click here.
All sensors have ‘jitter’, there are no clean movements
Jitter errors accumulate over time, so the Tactigon needs to be recalibrated regularly
gyro can be calibrated, planar axis accData calibration is very complicated
neutral position, offset on accData if board is flipped
using waypoints/virtual grid/… to re-sync the sensor values with real position
calibration phase after initializing, lowPassFilter for permanent re-calibration
latency! What latency?
simple, straightforward gesture with starting and end point
using acceleration to detect position
state machine to model typical user interaction
e.g. curving gestures, switching directions mid-gesture, etc.
more complex math, combination of multiple sensors necessary, to model individual behaviour
combining multiple gestures
time threshold between gestures
anticipate gestures through decision tree (advanced: Hidden Markov Model) to minimize latency
stable work environment;
Sometimes, compiling your sketch will suddenly fail because the IDE doesn’t recognize the board anymore. If that happens, navigate to C:\Users\YOUR_USERNAME\AppData\Local\Arduino15\packages\Next-package\hardware\stm32
If there is more than one subfolder, delete all but the most recent one.
boot loader windows 10, max baud rate (new boot loader available)
linker error with long path names and German Umlaut (fix at 115k Baud availble)
tools and gadgets available (eg. “plotter” TactigonAll, Cube-Demo)