Online Morphological Adaptation for Tactile Sensing Augmentation

Hughes, Josie; Scimeca, Luca; Maiolino, Perla; Iida, Fumiya

doi:10.3389/frobt.2021.665030

Cited by 10 publications

(6 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Then, we evaluated the information loss by analyzing what fraction of the original data variance was retained as a function of the number of considered principal components. Several other dimensionality reduction techniques could have been implemented for this purpose, such as t-SNE ( Maaten and Hinton, 2008 ), but we decided to implement PCA because it is widely used in filter-based tactile sensing ( Hughes et al, 2021 ).…”

Section: Methodsmentioning

confidence: 99%

“…Noticeable examples include the usage of hot melt adhesive to reshape the sensor morphology ( Nurzaman et al, 2013) and of liquid sensors able to tune dynamic range and sensitivity ( Liao et al, 2015) . Some studies focused precisely on online stiffness adaptation ( Hughes et al, 2021 ; Costi et al, 2022b) , highlighting how strongly the mechanical properties of the filter’s material can influence the embodied intelligence of the filter itself and, in turn, the task of tactile sensing. However, once again, little to no attention was given to the role of the environment.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

How the Environment Shapes Tactile Sensing: Understanding the Relationship Between Tactile Filters and Surrounding Environment

2022

Self Cite

View full text Add to dashboard Cite

The mechanical properties of a sensor strongly affect its tactile sensing capabilities. By exploiting tactile filters, mechanical structures between the sensing unit and the environment, it is possible to tune the interaction dynamics with the surrounding environment. But how can we design a good tactile filter? Previously, the role of filters’ geometry and stiffness on the quality of the tactile data has been the subject of several studies, both implementing static filters and adaptable filters. State-of-the-art works on online adaptive stiffness highlight a crucial role of the filters’ mechanical behavior in the structure of the recorded tactile data. However, the relationship between the filter’s and the environment’s characteristics is still largely unknown. We want to show the effect of the environment’s mechanical properties on the structure of the acquired tactile data and the performance of a classification task while testing a wide range of static tactile filters. Moreover, we fabricated the filters using four materials commonly exploited in soft robotics, to merge the gap between tactile sensing and robotic applications. We collected data from the interaction with a standard set of twelve objects of different materials, shapes, and textures, and we analyzed the effect of the filter’s material on the structure of such data and the performance of nine common machine learning classifiers, both considering the overall test set and the three individual subsets made by all objects of the same material. We showed that depending on the material of the test objects, there is a drastic change in the performance of the four tested filters, and that the filter that matches the mechanical properties of the environment always outperforms the others.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

How the Environment Shapes Tactile Sensing: Understanding the Relationship Between Tactile Filters and Surrounding Environment

2022

Self Cite

View full text Add to dashboard Cite

show abstract

“…There is limited exploration of how the sensory design affects the controller and the resultant performance. Whilst there has been some exploration of algorithms for topology optimization or morphology optimization of soft sensors [21,35], this largely focuses on optimizing to improve the reconstruction of tactile information opposed to optimizing for control purposes.…”

Section: Ease Of Simulation Sim/real Experiments Boundarymentioning

confidence: 99%

Leveraging Embodied Intelligence for Dexterous Robotic Manipulators Through Iterative Co-design

Junge

Hughes

2022

IOP Conf. Ser.: Mater. Sci. Eng.

Self Cite

View full text Add to dashboard Cite

The role of embodied intelligence (EI) has the potential to overcome current limitations in the fabrication, control, and resulting behavior to create robust and effective dexterous robotic manipulators. To develop hands that truly exploit EI, we must design hands by considering the entire system: the physical body, sensory systems, and the brain (the controller). However, we lack clear approaches and methods that enable this system level design for hands. We introduce an iterative approach for co-design which seeks to utilize simulation and real world evaluation to maximize the performance by distributing EI across the different elements of the system. To achieve this vision we require hands that can be rapidly fabricated with variability in the design space. Thus, to further the development of robotic hands that utilize EI we need streamlined fabrication pipelines which incorporate spatially distributed sensors, complex geometries and materials, and control distributed at the sensory-motor and high task planning domains.

show abstract

“…Authors in [17] attempted to alter the layered rubber skin of a vision-based tactile sensor, which contains a number of markers on it, in order to vary the human-robot haptic interaction for control purposes. Hughes et al [18] proposed a changeable jamming-based filter to enhance successful rate of tactile discrimination task. This work has proposed that, instead of trying to optimize design in advance, the sensor body should be able to adapt itself continuously and dependently on the sensing task.…”

Section: Introductionmentioning

confidence: 99%

Tactile Resilience of Sensory Whisker by Adaptive Morphology

et al. 2022

Self Cite

View full text Add to dashboard Cite

Nature is featured by the resiliency, which enables adaptivity to sudden change under many circumstances. Meanwhile, the resiliency in robotic systems is far from comparable to that of the nature. If a robot is partially damaged, often the whole system fails to operate properly. While some approaches have been proposed, the majority of them are focusing on updating the control policy. Such approach, while rather complex, is not always applicable to mechanical damage of the robot body, especially parts that continuously interact with the surrounding environment. In the previous works [1] [2], we introduced an artificial whiskered sensor that exhibited resilience against physical damage by active change of its morphology around the placement of sensory elements (strain gauges), which allowed compensation of location sensing when the whisker was trimmed. In this paper, we extend the approach by using the whisker sensor for texture discrimination tasks. We demonstrate that changing the morphology of the whisker again helps to reduce mismatching between prior knowledge in the frequency/time domain of the sensory signal. This allows the sensory whisker to recover the tactile perception on texture discrimination after the whisker is partially damaged. Furthermore, we also observe that using adaptive sensor morphology would augment tactile perception without the need of computationally expensive recognition and re-classification. This work is expected to shed a light on a new generation of robots that automatically work in the open world where self-maintenance against uncertainties is needed.

show abstract

Online Morphological Adaptation for Tactile Sensing Augmentation

Cited by 10 publications

References 30 publications

How the Environment Shapes Tactile Sensing: Understanding the Relationship Between Tactile Filters and Surrounding Environment

How the Environment Shapes Tactile Sensing: Understanding the Relationship Between Tactile Filters and Surrounding Environment

Leveraging Embodied Intelligence for Dexterous Robotic Manipulators Through Iterative Co-design

Tactile Resilience of Sensory Whisker by Adaptive Morphology

Contact Info

Product

Resources

About