HackSpace – September 2019

LENS

papers that proposed how the worm
moves (locomotion), and forages for food.
Since no existing robot incorporated both
these ideas, it seemed like a good plan to
build a robot that modelled them.
In the spring of 2017, Australian
robot-builder Shane Gingell joined the
project, and he and I proceeded to forge
ahead. We ended up with two versions of
the C. elegans robot. The first is a
Raspberry Pi processor implementation,

and the second is an ESP32 MicroPython
system on a chip (SoC) implementation.
Both implementations are a combined
effort. Shane spearheaded the design and
initial build, and I built the versions used for
external demos, as well as supplying
software to run the simulation.

LOCOMOTION

The first version was based on a Raspberry

Pi board, and accomplished one of the

goals: locomotion.

The robot consists of nine articulated

segments, which is a simplification from

the twelve segments in the real worm.

Each is segment mounted on a pair of

wheels. Locomotion is achieved, as it is in

C. elegans, by moving in a snake-like

manner that relies on surface friction. The

wheels are hence not powered and exist

to provide a suitable contact surface with

the ground.

Each segment is a 3D-printed component

that articulates with its neighbours via

servos. The electronic components are

mounted on platforms fastened to several

of the segments. We both purchased and

assembled Tarantula 3D printers to print

the parts. However, considering that 3D

printing services are typically easy to

obtain, and in hindsight, dealing with the

challenges of DIY printing, building, and

operating a printer did delay the completion

of the robot (personally speaking!).

The Raspberry Pi Zero W is a full-fledged

microprocessor that included wireless

communication capability. A PWM board

Above

The worm body designed

and ready to be 3D-printed

Future implementations

These could include:

• Touch response. C. elegans responds to
  touch on its nose by reversing direction.


• A Jupyter Notebook to provide a
  programming interface to the robot. This
  might also support software exercises
  related to C. elegans, such as how the
  neural network can be optimised to
  achieve sensorimotor coordination for
  touch response.

Above

The head section of the worm holds

the distance sensors

Since no existing robot incorporated both

these ideas, it seemed like a good plan to

build a robot that modelled them