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Andre Farinha

Publications and source records attributed to Andre Farinha.

3 recordsLinked to original sources

Graph-Based Design of Soft Grippers with Multi-Objective Quality-Diversity Optimisation

Effective manipulation across diverse objects is critical for applications ranging from agricultural harvesting to laboratory and domestic automation. While the inherent compliance of soft robotics is well suited to this challenge, designing grippers that generalize across tasks remains difficult due to the vast design space of continuum mechanics and the risk of overfitting to specific scenarios. We propose a graph-based design space for representing soft structures and mechanisms, coupled with a multi-objective, diversity-driven genetic optimization framework that explicitly promotes solution variety throughout the design process. Using multiple grasping scenarios during optimization, we study how task diversity influences the emergence of generalization to unseen objects and contact conditions. Our results show that optimization over a sufficiently diverse set of grasping cases leads to designs with emergent generalization, exhibiting improved robustness compared to task-specific solutions on novel scenarios. These findings suggest that diversity-driven optimization offers a principled pathway toward general-purpose soft grippers, aligned with the adaptable nature of soft robotics.

cs.RO

Programmable Telescopic Soft Pneumatic Actuators for Deployable and Shape Morphing Soft Robots

Soft Robotics presents a rich canvas for free-form and continuum devices capable of exerting forces in any direction and transforming between arbitrary configurations. However, there is no current way to tractably and directly exploit the design freedom due to the curse of dimensionality. Parameterisable sets of designs offer a pathway towards tractable, modular soft robotics that appropriately harness the behavioural freeform of soft structures to create rich embodied behaviours. In this work, we present a parametrised class of soft actuators, Programmable Telescopic Soft Pneumatic Actuators (PTSPAs). PTSPAs expand axially on inflation for deployable structures and manipulation in challenging confined spaces. We introduce a parametric geometry generator to customise actuator models from high-level inputs, and explore the new design space through semi-automated experimentation and systematic exploration of key parameters. Using it we characterise the actuators' extension/bending, expansion, and stiffness and reveal clear relationships between key design parameters and performance. Finally we demonstrate the application of the actuators in a deployable soft quadruped whose legs deploy to walk, enabling automatic adaptation to confined spaces. PTSPAs present new design paradigm for deployable and shape morphing structures and wherever large length changes are required.

cs.RO

3D Printable Soft Liquid Metal Sensors for Delicate Manipulation Tasks

Robotics and automation are key enablers to increase throughput in ongoing conservation efforts across various threatened ecosystems. Cataloguing, digitisation, husbandry, and similar activities require the ability to interact with delicate, fragile samples without damaging them. Additionally, learning-based solutions to these tasks require the ability to safely acquire data to train manipulation policies through, e.g., reinforcement learning. To address these twin needs, we introduce a novel method to print free-form, highly sensorised soft 'physical twins'. We present an automated design workflow to create complex and customisable 3D soft sensing structures on demand from 3D scans or models. Compared to the state of the art, our soft liquid metal sensors faithfully recreate complex natural geometries and display excellent sensing properties suitable for validating performance in delicate manipulation tasks. We demonstrate the application of our physical twins as 'sensing corals': high-fidelity, 3D printed replicas of scanned corals that eliminate the need for live coral experimentation, whilst increasing data quality, offering an ethical and scalable pathway for advancing autonomous coral handling and soft manipulation broadly. Through extensive bench-top manipulation and underwater grasping experiments, we show that our sensing coral is able to detect grasps under 0.5 N, effectively capturing the delicate interactions and light contact forces required for coral handling. Finally, we showcase the value of our physical twins across two demonstrations: (i) automated coral labelling for lab identification and (ii) robotic coral aquaculture. Sensing physical twins such as ours can provide richer grasping feedback than conventional sensors providing experimental validation of prior to deployment in handling fragile and delicate items.

cs.RO