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First Look at the Xaxxon Open Lidar Project

Here’s a couple pics and a short video of our latest product: the Xaxxon Open Lidar sensor! It’s a USB powered rotational laser scanner with open software and hardware, intended for use with mobile robots and simultaneous-location-and-mapping (SLAM) applications.

Xaxxon OpenLidar prototype

Xaxxon OpenLidar cad

The sensor has a simple mechanical design, using the proven Garmin LIDAR-Litev3 laser distance measurement sensor, wired through a rotational slip ring, with stepper motor drive, two 3D printed frame parts, and an Arduino compatible PCB. Power and communication are delivered via USB cable.

Initial ROS drivers are up on Github, with dynamically configurable settings including:
-RPM (10-250, 180 default)
-Sample rate (up to 750Hz)
-Range limits (up to 40 meters, even in sunlight!)

We’re working on adding this unit to our online shop now, with all the details, circuit schematics, and printed part STL downloads. It will be available as a fully assembled and tested sensor, and a 3D-print-your-own kit.

Of course, there is also an Oculus Prime accessory version in the works!


Posted by xaxxon on April 29, 2019   ↑ back to top


New for 2019 - the Xaxxon POWER v2 PCB

The first of a few NEW Xaxxon products for 2019 is the POWER v2 PCB!

Xaxxon POWER v2 PCB

This battery charging and system power management board adds new features to the 1st generation Xaxxon Power LiPo3S PCB, and fixes issues. Enhancements include:

  • No parasitic battery drain (ie., you no longer need to be careful about unplugging batteries when not using the system, which should lead to fewer premature pack deaths!)
  • Optional daisy-chaining of multiple boards and batteries for increased capacity
  • Second soft power shutoff mode added: you can now kill system power only, yet keep the 5V microcontroller alive (drawing very little power), and optionally bring system power back up after specified delay
  • Optional isolated battery-only power out (eg., for 12V motors to never experience high wall power voltages)
  • Higher wall power voltages accepted, up to 20V
  • Protection diode and 5A fuse now on-board, simplifying wiring

Board Dimensions/Example Setup/Typical Wiring Diagram:
xaxxon power v2 connection diagram

All new Xaxxon robots will be shipped with this board pre-installed, along with an Oculusprime software update that makes use of the second soft-power shutoff mode, to add a ‘drownproofing’ feature:
For lost robots that are unable to dock, with no remote help immediately available – instead of the usual powering down completely when the battery is depleted, the PCB will optionally power down the host system only, while leaving its microcontroller alive, then it will bring the host system back up every hour on the hour for 5 minutes, to see if any remote help is available.

The board is AVAILABLE NOW for purchase from our web store, for general mobile robotics projects, and DIY mobile PC projects. The previous generation board is still available (on sale!) while supplies last.

Bonus for current Xaxxon robot owners: if you want to upgrade to this new board you’re eligible for a discount! If interested, please contact us


Posted by colin on January 20, 2019   ↑ back to top


Updated MALG PCB version 3

xaxxon MALG PCB rev3

We’ve once again updated our multi function differential drive robot MALG PCB — it retains the same basic functionality with slightly improved microcontroller power decoupling/smoothing, and a few layout changes.

Gone is the ancient 4 pin Molex jack found in the previous MALG — apparently the original Molex ‘Mate-N-Lok’ style dates back to 1963! The Molex cable was being used simply as a way to get 5V power from a motherboard, and to not be limited by the 500mA maximum supplied through the USB cable. Instead, with the J4205-ITX and J5005-ITX motherboards supplied with Oculus Prime SLAM Navigator robots, we’re now running a single lead from the motherboards’ +5V pin found in its chassis speaker header.

For flexibility we’re staying with use of Pololu daughter boards for the gyro. As well there is now an alternate gyro header for optional use of latest generation Pololu gyros and IMUs.
The photo below is of a heavily modified SLAM Navigator sporting a second MALGv3, equipped with a 9-DOF Pololu AltIMU-10:

xaxxon MALG with AltIMU-10 v4 IMU

It’s running our modified version of the Razor_IMU_9dof ROS package with Attitude Heading Reporting System (AHRS) firmware.

Other changes are:

  • Audio jack placement no longer interferes with the USB cable
  • Changed to the more common micro-B USB jack
  • Omit unused ‘FWD FLDLED circuit
  • Location change to one mounting hole

For more details and to buy the MALGv3 PCB, with or without gyro daughter board, go to the MALGv3 product page.


Posted by xaxxon on October 15, 2018   ↑ back to top


MALG PCB Back In Stock with New Gyro

xaxxon MALG PCB revB

The MALG (Motors-Audio-Lights-Gyro) multi function, Arduino compatible, differential drive robot PCB is back in stock!

Our remaining old MALGs had quality issues with their MAX21000 gyro ICs. So, otherwise perfectly good boards have been resurrected, with Pololu daughter boards sporting the L3GD20 three-axis angular rate sensor.

Performance-wise it seems there is no significant difference between the two gyros: by the specs the newer L3GD20 sensor has the edge, but they both ultimately provide super-accurate rotational odometry when used in mapping and auto-navigation. (The MALG PCB is standard equipment in our Oculus Prime mobile robots).

Expansion header pins that are occupied by the daughter board are still available via pass-thru pads on the underlying interface board, as detailed in the connection diagram:

xaxxon MALG PCB revB connection diagram
(click to enlarge)

More information on the MALG PCB (revB), including schematic and datasheet is available here. Firmware source code can be found in the github repo.


Posted by xaxxon on November 21, 2017   ↑ back to top


Oculus Prime Software Updated with 4G/LTE Connectivity

Development and testing is now complete for the Relay Server software addition, which allows remote operation of Oculus Prime mobile robots connected to the internet via mobile 3G/4G/LTE networks. It also allows operation behind NAT firewalls, or on any network where there is no ability to configure and forward ports necessary for general internet remote access.

All that is required is to run an instance of the Oculusprime Server application on a device connected to an unconstrained network. This will act as the ‘relay’ server, which you then configure the robot to connect to. When you want to remotely connect to the robot, you connect to the relay server instead, which relays commands and video from the robot seamlessly. The server can be running on any Linux system, including a Raspberry Pi, or within a virtual Linux environment on a Windows or OS X PC.

Now you can equip Oculus Prime SLAM Navigator or Pi Explorer with a smartphone or mobile wifi hotspot, and see how far you get driving around outside, free from the limited range of a wifi network (in fair weather, of course!)

This addition to the Oculusprime Server application has been on the to-do list for a long time, but has been put off because, well, it required a lot of boring network programming. (There always seemed to be something more exciting to work on, like testing out the newly-opened-sourced Google Cartographer ROS package.)


Summary of enhancements to Oculusprime Server version 0.8:

  • Relay server
  • Expanded network menu
  • Wifi Access Point Manager upgraded to version 0.914
  • Red5 streaming media server upgraded to version 1.07
  • Apache Tomcat web server upgraded to version 8.0.33
  • Updated power PCB firmware (auto power-off at 30%, reduce false positive errors)
  • Force disable navigation before auto-dock
  • Added calibraterotation command
  • Added no-battery-connected indicator to web browser UI
  • Minor bug fixes, optimisations


For software update instructions, see here.
For more details on running the relay server, see here.
Java 8 is now recommended, which has to be installed manually, see here for upgrade instructions.


Posted by xaxxon on October 25, 2016   ↑ back to top


Video: SLAM Navigator Autonomous Driving in Warehouse at Night

Watch an Oculus Prime SLAM Navigator unit drive itself around a warehouse at night:

The video shows the view through the remote web browser interface – the only user interaction is 3 clicks, selecting 2 waypoints then return to charging dock.

At around the 2:15 mark you can watch it close in and dock with its charging dock, which is tightly placed in a narrow slot between racks.

The map was created in one attempt by manually driving around the warehouse for 10 minutes, and was used in its original (un-edited) state.

Thanks to Shodor Industries for the video!


Posted by xaxxon on September 30, 2016   ↑ back to top


An Exploration of Stereo Vision SLAM Mapping - Early Prototype

Not too long ago, the availability of low cost depth sensors, suitable for mobile robot auto-navigation and SLAM mapping, had become a problem. Apple bought Primesense, and along with it the intellectual property behind the original Microsoft Kinect and Asus Xtion sensors. The excellent Asus Xtion RGBD camera, which was to be the main SLAM sensor for Oculus Prime, was discontinued. The Kinect 1 was still available in quantity, but it was bigger and heavier, and required separate 12V and 5V power.


And it somehow just looks wrong with a Kinect mounted to Oculus Prime:

kinect oculus prime mobile robot SLAM

So, we decided to explore using stereo vision as a possible option. A prototype robot was conjured, sporting two Lifecam Cinema cameras:

stereo SLAM mobile robot oculus prime


OpenCV’s Semi-Global-Block-Matching (SGBM) algorithm yielded decent looking depth data from combined images. Below left is the left camera view, and on the right is the disparity image generated with the cameras separated by a 60mm baseline – pixel intensity is proportional to distance from camera:

oculus prime stereo depth image test


Comparing the depth images from the stereo setup vs the Asus Xtion camera was looking promising (stereo image on top, Xtion image on bottom, left camera 2D image inset):

stereo vs RGBD depth camera


In practice however, with this stereo setup as the data source for ROS SLAM mapping, there were issues. The depth data was quite noisy for some surface textures, and depth accuracy wasn’t very good beyond a few meters. Also, the SGBM algorithm tends to cause data omission for large texture-less surfaces.

The image below shows a comparison of a plan view map of the same area, generated using the stereo setup on the left, and using the Asus Xtion depth camera on the right (using data from the horizontal plane only, and pure odometry to align the scans):

Stereo map on left, Xtion on right (click to enlarge)
stereo vs RGBD SLAM map

The stereo scan noise occasionally projected a small false obstacle, that would wreak havoc with the ROS path-planner, and the inaccuracy or omission of distant features would cause weak localisation (and a lost robot).

Another problem was the slow speed of the system: the OpenCV Java SGBM processing, along with all the other robot functions fighting for CPU time, would only yield 2 frames per second (the prototype stereo-bot had an Atom N2800 CPU), demanding that navigating robot speed be slowed way down, to reduce errors.

In retrospect, an integrated stereo solution like the Zed camera, with some on-board processing and tightly-calibrated cameras, would have been much more effective (if money was no object).

In the end, we stuck with the Asus Xtion, dwinding supply and all, in the hope that the near future would deliver a new low cost depth sensor with stable supply.
Luckily the Orbbec Astra came along just in time.


Posted by colin on June 23, 2016   ↑ back to top




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