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Fumiya Iida

Publications and source records attributed to Fumiya Iida.

21 records · Page 2Linked to original sources

Embedded Soft Sensing in Soft Ring Actuator for Aiding with theSelf-Organisation of the In-Hand Rotational Manipulation

This paper proposes a soft sensor embedded in a soft ring actuator with five fingers as a soft hand to identify the bifurcation of manipulated objects during the in-hand manipulation process. The manipulation is performed by breaking the symmetry method with an underactuated control system by bifurcating the object to clockwise or counter-clockwise rotations. Two soft sensors are embedded in parallel over a single soft finger, and the difference in the resistance measurements is compared when the finger is displaced or bent in a particular direction, which can identify the bifurcation direction and aid in the break of symmetry approach without the need of external tracking devices. The sensors performance is also characterised by extending and bending the finger without an object interaction. During an experiment that performs a break of symmetry, manipulated objects turn clockwise and counter-clockwise depending on the perturbation and actuation frequency, sensors can track the direction of rotation. The embedded sensors provide a self-sensing capability for implementing a closed-loop control in future work. The soft ring actuator performance presents a self-organisation behaviour with soft fingers rotating an object without a required control for rotating the object. Therefore, the soft fingers are an underactuated system with complex behaviour when interacting with objects that serve in-hand manipulation field.

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Reality-assisted evolution of soft robots through large-scale physical experimentation: a review

In this review we introduce the framework of reality-assisted evolution to summarize a growing trend towards combining model-based and model-free approaches to improve the design of physically embodied soft robots. In silico, data-driven models build, adapt and improve representations of the target system using real-world experimental data. By simulating huge numbers of virtual robots using these data-driven models, optimization algorithms can illuminate multiple design candidates for transference to the real world. In reality, large-scale physical experimentation facilitates the fabrication, testing and analysis of multiple candidate designs. Automated assembly and reconfigurable modular systems enable significantly higher numbers of real-world design evaluations than previously possible. Large volumes of ground-truth data gathered via physical experimentation can be returned to the virtual environment to improve data-driven models and guide optimization. Grounding the design process in physical experimentation ensures the complexity of virtual robot designs does not outpace the model limitations or available fabrication technologies. We outline key developments in the design of physically embodied soft robots under the framework of reality-assisted evolution.

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Agricultural Robotics: The Future of Robotic Agriculture

Agri-Food is the largest manufacturing sector in the UK. It supports a food chain that generates over £108bn p.a., with 3.9m employees in a truly international industry and exports £20bn of UK manufactured goods. However, the global food chain is under pressure from population growth, climate change, political pressures affecting migration, population drift from rural to urban regions and the demographics of an aging global population. These challenges are recognised in the UK Industrial Strategy white paper and backed by significant investment via a Wave 2 Industrial Challenge Fund Investment ("Transforming Food Production: from Farm to Fork"). Robotics and Autonomous Systems (RAS) and associated digital technologies are now seen as enablers of this critical food chain transformation. To meet these challenges, this white paper reviews the state of the art in the application of RAS in Agri-Food production and explores research and innovation needs to ensure these technologies reach their full potential and deliver the necessary impacts in the Agri-Food sector.

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