Super Mega Ultra Bot

DIY 4x4 ROS-enabled rover robot with BLDC hub motors

Rough BoM

• 30x30 aluminum extrusions
  • 4 meters should be enough
• 30x30 aluminum extrusion brackets and T-slot nuts & bolts
  • 40 should be enough
• Aluminum sheets
  • 2 sq. m should be enough
  • A simple way to cut aluminum sheets with just a knife
• 2x ODrive 3.6 56V
  • https://odriverobotics.com/shop/odrive-v36
• 12x 22uF capacitors for filtering hall signals to Odrive
  • Refer to this discusssion on ODrive forum.
• 4x geared bldc motor, 11 inch
  • Original link to the item seems dead. This seems to be the closest match, but make sure to look for one that has the axle sticking out only on one side, like hoverboard wheels.
  • This is the one I ordered. It has the model name phub-11hs, so you might have some luck searching with that. Don’t forget to try the Chinese web.
• Raspberry pi
• flysky fsi6b receiver + transmitter (optional)
  • I use this ROS package to publish cmd_vel from the RC reciever. To use this, you need to connect the receiver to the USB on the onboard computer (in my case a Raspberry Pi 4) using a uart/ttl usb converter. Refer to this page for more detailed information.
• 48v to 12v step down converter
  • Something like this should work. Power rating would depend on how many other peripheral devices (additional compute, sensors, networking, etc.) you would run, but 360W should be enough.
• 3D printed parts used:
  • https://www.thingiverse.com/nhooram/collections/smub
• wires
• XT60 connectors
• fans for cooling
• emergency stop
• switches
• power meter (optional)
• LEDs for front light (optional)
• usb cables
• ethernet cable
• wifi router
• arduino nano (for rear blinker): subscribes to cmd_vel, changes colors on rear lights
• 2x neopixel ring (for rear blinker, 12 led)

Wiring Diagram

ODrive thermal with fans

• Mapping using Rtabmap with D455 and 2d lidar
• Navigation using move_base

Make 3

• uses old dynamixel RX28 servos.
• 18 dof
• RPLidar A1 2d Lidar
• Jetson Xavier NX
• Intel Realsense d455 depth camera
• runs openshc ROS package (https://github.com/csiro-robotics/syropod_highlevel_controller)
• tip ground contact sensors (tactile switches) using rosserial_arduino
• wrote a ROS node that publishes the tip sensor data in a format openshc understands.
• want to make it into a decent rough terrain crawler
• servos seem to reach thermal limit quickly - added fans to motors
• 2d and 3d slam using a 2d lidar and a depth camera with hector mapping and rtabmap packages

Videos

Indoor 3d SLAM with d455 and exploring various sensor data

Here I manually control the hexapod with a ps4 controller around the room. ROS master node is running on the bot on a Jetson NX. It has a 2D lidar and a Realsense depth camera. It runs the openshc package for hexapod control, and rtabmap for 3D SLAM. Visualization is done on a desktop machine on the same network.

Long video of testing the admittance controller

Short screen capture of exploring variables on rviz/rqt

Outdoor flat forest floor traverse test

Some Pictures

Side by side with Make 2

Assembled

Close up

Visualization of topic data from openshc with rqt and rviz

Added fans

Silicon anti slip cap (and the mould)

Make 2

• uses dynamixel XL430 servos.
• 24 dof
• the same control system as Make 1.
• runs on a Jetson Xavier NX.
• has a 2d lidar ~ 10Hz
• has a stereo depth camera (realsense D435i)
• experimented with running SLAM stack on ros using the two sensors: https://www.youtube.com/watch?v=-N8fmfxq5lY
• played around with hector slam for 2d lidar, rtabmap, VINS-Fusion (https://github.com/HKUST-Aerial-Robotics/VINS-Fusion)
• got familar with the high level organization of the ROS stack.
• later removed one dof from each leg for faster IK computation.
• control software capability (even ground mode): https://www.youtube.com/watch?v=li7Eii5mxpQ

4 DoF Legs

3 DoF Legs

Make 1

Inspired by Smallp Tsai’s hexapod v2.1 video

Drawings

Notes

• used a raspberry pi zero sized board
• has an IMU
• 24 dof
• control software written in python using numpy, scipy, servo controller library.
• 4dof legs -> no analytical solution for inverse kinematics. Implemented an iterative method for 4dof leg IK solution. Also can use an optimizer from scipy.optimize.
• basics of the endeffector position based control algorithm code in this jupyter notebook
• power system is janky - sometimes when the servos draw too much power at once, the sbc reboots.
• learned to use Fusion360 to design parts needed using a 3D printer.
• parts:
  • banana pi zero
  • 7x buck converter
  • GY210 IMU
  • 2s lipo
  • 24x towerpro MG90B servos
  • 2x 12ch pwm controller board
• one buck converter provides 5v to the sbc
• the servo controller boards get power from sbc
• four servos (one leg) get power from one buck converter
• sbc, servo controller boards, and the IMU talk through i2c

Pictures

Videos

3 DoF Legs

4 DoF Legs

BoM

• 6x Dynamixel XL430 (~300 EUR)
• 2x Dynamixel 2XL430 (~200 EUR)
• 1x RPLIDAR A1 (~100 EUR)
• 1x Intel Realsense D4xx Camera (200 ~ 300 EUR)
• Jetson Nano / Xavier NX / Raspberry Pi (50 ~ 400 EUR)
• 3d printed parts
• 12V DC step down converter (< 10 EUR)
• (5V DC step down converter, necessary for Jetson Nano & Raspberry Pi) (< 10 EUR)
• screws (~ 30 EUR)
• 4s Lipo Battery

With the choice of the board	Total cost around
Jetson Xavier NX	$1250
Jetson Nano	$1000
Raspberry Pi	$920

Arm configurations

Navigation 1

• High camera position, better position of the camera for 3d SLAM
• More camera shaking during movement from backlash and tolerances

Navigation 2

• Lower camera position, worse position of the camera for 3d SLAM
• Less camera shaking during movement from backlash and tolerances