Dynamical Mechanical Metamaterials for Path Generation

Master Thesis (2024)
Author(s)

T.E. Vreugdenhil (TU Delft - Mechanical Engineering)

Contributor(s)

D. Farhadi Machekposhti – Mentor (TU Delft - Mechatronic Systems Design)

Giovanni Bordiga – Mentor (Harvard University)

Farbod Alijani – Graduation committee member (TU Delft - Dynamics of Micro and Nano Systems)

Faculty
Mechanical Engineering
More Info
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Publication Year
2024
Language
English
Graduation Date
27-11-2024
Awarding Institution
Delft University of Technology
Programme
['Mechanical Engineering | High-Tech Engineering']
Faculty
Mechanical Engineering
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Abstract

Many robotic applications require moving an end-effector through intricate closed-loop paths for object manipulation or locomotion. Conventionally, rotary-actuated rigid-link mechanisms perform this task successfully. However, several drawbacks, such as wear, play, and assembly difficulties, limit their performance. In high-speed applications, these rigid and often bulky links require high accelerations, leading to high power usage or the need for dynamic balancing, further complicating the mechanism. Rigid mechanisms are not the only ones that generate paths; compliant mechanisms are also widely used. However, compliant hinges cannot undergo complete rotations by definition, making cyclic actuation impossible. As a result, creating closed-loop paths typically requires multiple actuators—one per end-effector degree of freedom—adding to power demands and complexity. In contrast, closed-loop deformations can occur when dynamically actuating a soft body with a single actuator. We can create customizable soft bodies that leverage internal dynamics by structuring this soft body with a mechanical metamaterial made of tessellated compliant cells and designing its internal geometry. This research explores how these dynamics can be harnessed for path generation within mechanical metamaterials. Through multi-objective optimization, we embed reprogrammable control strategies within the metamaterial geometry, enabling adaptive responses to actuation frequency and amplitude for complex behaviors. We validate these designs with tabletop prototypes, building up to a self-propelled, walking prototype—a step toward autonomous robotic metamaterials.

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