Julian Jocque

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About

Julian Jocque is a researcher specializing in soft robotics, tensegrity structures, and evolutionary computation, with a particular focus on the intersection of mechanical design and autonomous locomotion. His most notable contributions center on tensegrity robots — lightweight, resilient structures composed of cables and rigid members — and their application to emerging challenges in robotics such as search-and-rescue operations and field-deployable systems. Jocque's most impactful work, "Evolution of Locomotion on a Physical Tensegrity Robot" (2014), has garnered over 40 citations across its publications, demonstrating significant community interest in his approach of using evolutionary algorithms to generate locomotion strategies for physically complex robotic platforms. Rather than simplifying the challenging dynamics inherent to tensegrity systems, his research embraces that complexity as an asset. This philosophy is further explored in his work on morphological computation, where he demonstrates how the mechanical properties of tensegrity robots can themselves contribute to control and actuation — a paradigm shift from conventional robotics. By showing that structural complexity can be computationally advantageous rather than merely an obstacle, Jocque has helped lay conceptual groundwork for a more biologically inspired approach to robot design and control.