Dynamics and Control of a 3D Printed Walking Robot

Stefanov, A. A.; Chavdarov, Ivan; Nedanovski, Dimitar; Boiadjhiev, George

doi:10.23919/softcom.2019.8903684

Cited by 2 publications

(1 citation statement)

References 11 publications

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“…The robot’s ability to passively adapt to high obstacles in order to overcome them is discussed. The authors of [ 29 ] present numerous experiments with 3D-printed models of the robot with different shapes and materials of the feet, which lead to an increase in its movement capabilities in a complicated environment. The dynamics of the robot is developed in [ 30 ].…”

Section: Background and Related Workmentioning

confidence: 99%

A Strategy for Controlling Motions Related to Sensory Information in a Walking Robot Big Foot

Chavdarov

Yovchev

Miteva

et al. 2023

Sensors

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Acquiring adequate sensory information and using it to provide motor control are important issues in the process of creating walking robots. The objective of this article is to present control algorithms for the optimization of the walking cycle of an innovative walking robot named “Big Foot”. The construction of the robot is based on minimalist design principles—only two motors are used, with which Big Foot can walk and even overcome obstacles. It is equipped with different types of sensors, with some of them providing information necessary for the realization of an optimized walk cycle. We examine two laws of motion—sinusoidal and polynomial—where we compare the results with constant angular velocity motion. Both proposed laws try to find balance between minimizing shock loads and maximizing walking speed for a given motor power. Experimental results are derived with the help of a 3D-printed working prototype of the robot, with the correct realization of the laws of motion being ensured by the use of a PD controller receiving data from motor encoders and tactile sensors. The experimental results validate the proposed laws of motion and the results can be applied to other walking robots with similar construction.

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Section: Background and Related Workmentioning

confidence: 99%