Robotic Sorting of Ovine Offal: Discussion of a Soft Peristaltic Approach

StommelMartin,; Wang, Xu; KadmiryBourhane,

doi:10.1089/soro.2014.0007

Cited by 25 publications

(6 citation statements)

References 66 publications

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“…More recently, Jørgensen et al [8] segmented gallbladders in chicken livers from images acquired at two visible wavelengths. Stommel et al [18] envisaged a system for robotic sorting of ovine offal that would involve automatic recognition of multiple organs.…”

Section: Application Domainmentioning

confidence: 99%

Weighted atlas auto-context with application to multiple organ segmentation

Amaral

Kyriazakis

McKenna

et al. 2016

2016 IEEE Winter Conference on Applications of Computer Vision (WACV)

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Difficulties can arise from the segmentation of threedimensional objects formed by multiple non-rigid parts represented in two-dimensional images. Problems involving parts whose spatial arrangement is subject to weak restrictions, and whose appearance and form change across images, can be particularly challenging. Segmentation methods that take into account spatial context information have addressed these types of problem, which often involve image data of a multi-modal nature. An attractive feature of the auto-context (AC) technique is that a prior "atlas", typically obtained by averaging multiple label maps created by experts, can be used as an initial source of contextual data. However, a prior obtained in this way is likely to hide the inherent multi-modality of the data. We propose a modification of AC in which a probabilistic atlas of part locations is iteratively improved and made available as an additional source of information. We illustrate this technique with the problem of segmenting individual organs in images of pig offal, reporting statistically significant improvements in relation to both conventional AC and a state-of-the-art technique based on conditional random fields.

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Section: Application Domainmentioning

confidence: 99%

Weighted atlas auto-context with application to multiple organ segmentation

Amaral

Kyriazakis

McKenna

et al. 2016

2016 IEEE Winter Conference on Applications of Computer Vision (WACV)

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“…The last decade has witnessed a large impetus in the field of soft robotics, with potential applications in rehabilitation and healthcare [1], medical invasive surgery [2], undersea/space search and exploration [3], food handling [4] and advanced manufacturing [5]. Built of compliant materials, soft robots exhibit muscle-like behavior, resulting in a large number of degrees of freedom.…”

Section: Introductionmentioning

confidence: 99%

A soft robot capable of 2D mobility and self-sensing for obstacle detection and avoidance

Qin

Tang

Gupta

et al. 2018

Smart Mater. Struct.

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Soft robots have shown great potential for surveillance applications due to their interesting attributes including inherent flexibility, extreme adaptability, and excellent ability to move in confined spaces. High mobility combined with the sensing systems that can detect obstacles plays a significant role in performing surveillance tasks. Extensive studies have been conducted on movement mechanisms of traditional hard-bodied robots to increase their mobility. However, there are limited efforts in the literature to explore the mobility of soft robots. In addition, little attempt has been made to study the obstacle-detection capability of a soft mobile robot. In this paper, we develop a soft mobile robot capable of high mobility and self-sensing for obstacle detection and avoidance. This robot, consisting of a dielectric elastomer actuator as the robot body and four electroadhesion actuators as the robot feet, can generate 2D mobility, i.e. translations and turning in a 2D plane, by programming the actuation sequence of the robot body and feet. Furthermore, we develop a self-sensing method which models the robot body as a deformable capacitor. By measuring the real-time capacitance of the robot body, the robot can detect an obstacle when the peak capacitance drops suddenly. This sensing method utilizes the robot body itself instead of external sensors to achieve detection of obstacles, which greatly reduces the weight and complexity of the robot system. The 2D mobility and self-sensing capability ensure the success of obstacle detection and avoidance, which paves the way for the development of lightweight and intelligent soft mobile robots.

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“…Indeed, the soft-bodied conveyors or feeders reported in literature are mostly shaped as pneumatically deformable soft surfaces capable of moving objects on a horizontal plane. In this regard, key examples are the fluid-based systems such as the "Festo Wavehandling" platform [6], which features a soft surface actuated by a pneumatic system that enables for the displacement of round objects through a wave-like motion, and the soft platform developed by Stommel et al [7], featuring a pneumatically-induced peristaltic motion enabling it for ovine offal sorting. Another interesting device for material handling is described in the work of Mosadegh et al [8] who presented a reconfigurable manifold designed for controlling pneumatically actuated soft machines, based on a computer-controlled braille display.…”

Section: Introductionmentioning

confidence: 99%

Design and proof of concept for multi degree of freedom hydrostatically coupled dielectric elastomer actuators with roto-translational kinematics for object handling

Acutis¹,

Calabrese²,

Baù³

et al. 2018

Smart Mater. Struct.

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In this article we present an upgraded design of the existing push-pull Hydrostatically Coupled Dielectric Elastomer Actuator (HC-DEA) for use in the field of soft manipulators. The new design has segmented electrodes, which stand as four independent elements on the active membrane of the actuator. When properly operated, the actuator can generate both out of plane and in plane motions resulting in a multi-degrees of freedom soft actuator able to exert both normal pushes (like a traditional HC-DEA) and tangential thrusts. This novel design makes the actuator suitable for delicate flat object transportation. In order to use the actuator in soft systems, we experimentally characterized its electromechanical transduction and modeled its contact mechanics. Finally, we show that the proposed actuator can be employed as a modular unit to develop active surfaces for flat object roto-translation.

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Robotic Sorting of Ovine Offal: Discussion of a Soft Peristaltic Approach

Cited by 25 publications

References 66 publications

Weighted atlas auto-context with application to multiple organ segmentation

Weighted atlas auto-context with application to multiple organ segmentation

A soft robot capable of 2D mobility and self-sensing for obstacle detection and avoidance

Design and proof of concept for multi degree of freedom hydrostatically coupled dielectric elastomer actuators with roto-translational kinematics for object handling

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