The Project

The S.A.R.T. is designed as a disposable, rapidly manufactured and cheap remote inspection vehicle that can be deployed in any situation where it is difficult or dangerous to send in human personnel. From search and rescue to disaster response to inspection of tunnels and pipelines, S.A.R.T. robots are equipped with arrays of sensors and cameras to report the situation to personnel on the scene.

Open Source

The S.A.R.T. project is completely open source. All our code and design files, as well as tutorials and useful information is available on our website, GitHub and Thingiverse. By keeping the project open, we hope to faciliate the development of rapidly manufactured first response robots worldwide, contributing to the global goal of saving lives.

S.A.R.T Interface

The S.A.R.T robot is controlled via a dashboard called the S.A.R.T Interface. Features include multiple video streams, providing a 360° view, live sensor data including thermal imagery, direct access to the robot through SSH console, and much more. Users never have to access the S.A.R.T hardware directly – everything can be done within the interface. See the demo here!

Complete Documentation

We provide extensive documentation on all our design and construction processes when it comes to coding, modelling, building, and coming up with new ideas. You could build your own S.A.R.T simply using the information provided in our daily blog.

Also available is the comprehensive 2020 Q1 S.A.R.T. TDM.

The Future

We have many plans to expand the versatility of the S.A.R.T robot. We are creating a “base model” that other people can develop on top of thanks to our Open Source philosophy.

Awards & Recognition

We often enter our robots in competitions such as RoboCup. We have received awards and recognition for a number of achievements and advances.

  • Tied 1st Place – Rapidly Manufactured Rescue League, RoboCup 2016, Leipzig, Germany
  • 1st Place – Rapidly Manufactured Rescue League, RoboCup 2017, Nagoya, Japan
  • Open Source Award – Rapidly Manufactured Rescue League, RoboCup 2017, Nagoya, Japan
  • Open Source and Innovation Award – Rapidly Manufactured Rescue League, RoboCup 2018, Montréal, Canada


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S.A.R.T Mark IV

Drive System2x Dynamixel AX-18A Servo
Computational UnitNVIDIA Jetson Nano
Central ProcessorQuad-core ARM A57 @ 1.43 GHz
Onboard StoragemicroSD
RAM4 GB 64-bit LPDDR4
Camera System3x ELP 5MP HD USB Camera
1x Pimoroni MLX90640 Thermal Camera
Mapping SystemLDS-01 LIDAR Laser Distance Sensor
Additional SensorsAir Quality (VOC and eCO2), Temperature
Human CommunicationTwo-way Stereo Audio
Manipulator60 cm Arm & Claw, 4 Degrees of Freedom
Control SystemS.A.R.T. Interface (Keyboard, Controller)

S.A.R.T Mark III

Drive System4x Dynamixel AX-18A Servos
Computational UnitUDOO x86 Ultra
Central ProcessorIntel Pentium N3710 @ 2.56GHz x4
Onboard Storage32GB Integrated eMMC
Camera System4x ELP 5MP USB Camera, 1x Thermal Camera
Mapping System4x Adafruit VL53L0X Time-Of-Flight Sensor
Additional SensorsAir Quality (VOC and eCO2), Temperature
Human CommunicationTwo-way Audio
Control SystemS.A.R.T. Interface

S.A.R.T Mark II

Drive System4x Dynamixel AX-18A Servos
Computational UnitIntel NUC NUC5CPYH
Central ProcessorIntel Celeron N3050 @ 2.16GHz x2
Onboard Storage120GB SAMSUNG SSD
Camera SystemoCam 5MP USB 3.0 Camera
Mapping System4x SHARP GP2Y0A21YK0F Infared Sensor
Additional SensorsTemperature, Accelerometer, Compass
Human CommunicationText to Speech, Speech to Text
Control SystemS.A.R.T. Interface

S.A.R.T Mark I

Drive System4x Dynamixel AX-12A Servos
Computational UnitRaspberry Pi 3
Onboard Storage32GB SD
Camera SystemRaspberry Pi Camera Board
Control SystemPlayStation Controller

Our Team

S.A.R.T. Alumni

S.A.R.T. Development Blog

UBECcer Watch Out

Over the past few days we’ve made some exciting locomotion advancements. Connor created Sights motor wrapper plugins for RoboClaw and Roboteq motor controllers, Alex authored a new servo controller for the arm, and Jack jerry-rigged a system to run multiple...

Target Translation

On Tuesday evening we had our first test of the new S.A.R.T. Series M robot with all systems functioning at the same time. During our tests we noticed some of the arm positions caused unnecessary strain on the servos, so...

Using Hardware Acceleration in VNC

‘Any sufficiently advanced technology is indistinguishable from magic.’ I’d like to slightly modify that statement to ‘Any solution to a technology problem that works for an inexplicable reason is indistinguishable from magic’. Here’s why: The S.A.R.T. recently acquired a pair...

Extracting a floor plan from a ZED Mini model using Blender

One of the requirements for the Major competition is to generate a top-down floor plan of the room in which the test takes place. Ideally, this would happen automatically, however until we get that working we can use the exported...

Unbending Bender

Today I worked mostly on testing and familiarizing myself with our development robot, which we as a team named ‘Bender’. To begin the day, I began driving Bender through our various practice courses whilst only navigating using the cameras. I...

Moving 4ward

Big success today as part of our community outreach program “S.A.R.T. Junior”, we got 4 motors working at once with a H bridge and a Raspberry Pi. This simplified system was created to assist with new teams entering the rapidly...

Nvidia Jetson Nano with Intel Wireless AC PCIe WiFi

Here’s how we got our Jetson Nano working reliably with an Intel Wireless AC 3165 PCIe WiFi card. This post outlines the steps someone else used to solve this issue on the Nvidia developer forums, but the solution was spread...


For years, power has always been something we have constantly been seeking to improve. Most robots and other remote/portable applications utilise LiPo batteries. While flexible and providing lots of power in a small package, LiPo batteries do have a lot... forward – powered by Dell Technologies

Moving away from the challenging year that 2020 was for us all, S.A.R.T. was very fortunate to get the opportunity to partner with Dell Technologies to power our efforts moving into 2021. As a part of our partnership, Dell have...

S.A.R.T. Through The Ages Part Trois: The Renaissance

It was July of 2016, and by our rough calculations we had about twelve months to develop a reliable robot for the competition the next year in Nagoya, Japan.  We briefly discussed developing the robot out of a new material,...

S.A.R.T. Through The Ages Part The Second: The Dark Ages

Alex had returned from China with a plethora of ideas for potential improvements to the platform we were developing on, including both the hardware and software side of the robot. Ryan and Jack began working on what would eventually become...

S.A.R.T. Through The Ages Part 1: The Medieval Era

Greetings, everyone.  It’s been a while since I wrote a blog, I don’t think I’ve posted a blog since I became a member of the esteemed club known as the S.A.R.T. Alumni. I thought, with the introduction of a generation...

S.A.R.T. Team Description Materials for Q1 2020

Authors: Connor Kneebone, Alexander Cavalli, Jack Williams, Matthew Williams, Graham Stock, Charlotte Drury, Anthony Gambale, Michael Cavalli, Nathaniel Kneebone, Martin Hosking, Alexander Thorning Published: 20th of March, 2020 Abstract The Semi-Autonomous Rescue Team (herein known as the S.A.R.T.) is a...
New wheel hub in Fusion 360

A ‘Wheely’ Good Day Pt. IV

The wheels we made for the Mark III robot did pretty well. The new polyurethane tires were excellent, they had plenty of grip, were basically indestructible and they maintained their grip over many hours of use. The hubs worked pretty...

Unwrapping Sensor Wrappers – Part 2: Graphs

The SIGHTS software suite is designed to be very extensible when it comes to adding new sensors to your robot. We achieve this by using special Python classes called sensor wrappers to collect sensor data, and JavaScript classes called Graphs...

Unwrapping Sensor Wrappers – Part 1: Sensors

The SIGHTS software suite is designed to be very extensible when it comes to adding new sensors to your robot. We achieve this by using special Python classes called sensor wrappers to collect sensor data, and JavaScript classes called Graphs...

A Blog Post About Two-Way Audio

A brief history of two-way audio In previous years, we have used a few methods to do two-way audio. Initially we had a speech to text and back again system to transmit data. Needless to say, this was quite limiting...

Make It Yours: Configuring SIGHTS Part 2 (Advanced Configuration)

In “Make It Yours: Configuring SIGHTS Part 1” I showed you how to configure a basic SIGHTS-based robot. In this, the second part, I’ll go over the more complex configuration of Interface and Sensors. The Simple Bits Ok, I lied....