The manufacture and assembly of small-scale robotics can be expensive and time-consuming using traditional methods; especially when complex mechanisms are involved. By refining current additive manufacturing techniques a micro-scale walking robot can be 3D printed without the need for any complex mechanical assembly. The robot requires only the addition of simple circuitry and 2 motors, one for each of the 1 degree of freedom walking mechanisms before it is capable of being driven wirelessly. Once fully assembled, differential drive of the parallel leg sets allows for locomotion in any direction on a 2-D plane. The robot's compact size; just 62mm (x) x 38mm (y) x 88mm (z), and leg curvature makes travel possible through borehole/pipe diameters as low as 65mm. By pushing printer tolerances to the limit, complex mechanisms can work in Non-Assembly at a small scale. Through the application of these Non-Assembly techniques to field robots such as those intended for use in the Pipebots project could allow for the production of large swarms of robots quickly and affordably.

Small inspection robots can allow for the exploration of environments and the collection of data from dangerous or difficult to access areas. These robots can be custom built for specific tasks, but the design and assembly process for this can be costly, both in money and time. The use of 3D Printing in creating Non-Assembly mechanisms can assist in saving time and resources by reducing the number of different components required and removing the necessity for complex assembly tasks. This paper introduces a robot to explore the capabilities of this approach, by iterating on a previous example of a robot with Non-Assembly mechanisms. This explores how altering the size, mechanism type and accompanying control circuitry can affect the efficiency of the practice. Through developing on previous knowledge, this new walking robot improves on the previous iteration by creating a more robust and reliable system, more capable of effectively exploring challenging environments accurately, while still using practices designed to save on cost and production time.