Achieving Robotically Peeled Lettuce

Robotic technologies are being increasingly applied to agriculture, in particular to harvesting. Some types of produce such as iceberg lettuce require additional processing after harvesting in order to satisfy the needs of the end-user or customer. Lettuce must have its outer leaves removed, a task that is currently performed manually. The leaf removal task represents a challenging vision and manipulation problem: the lettuce is in a random pose on a flat surface, from which the outermost leaves must be removed quickly and without causing damage. This letter presents a novel vision pipeline and suction removal system that enables robotic lettuce leaf removal. A suction nozzle and control procedure are used for the removal itself, relying on the orientation estimation and stem detection provided by the vision pipeline. To the best of the author's knowledge, this is the first robotic lettuce leaf peeling system

Soft Morphological Computation

Soft Robotics is a relatively new area of research, where progress in material science has powered the next generation of robots, exhibiting biological-like properties such as soft/elastic tissues, compliance, resilience and more besides. One of the issues when employing soft robotics technologies is the soft nature of the interactions arising between the robot and its environment. These interactions are complex, and the their dynamics are non-linear and hard to capture with known models. In this thesis we argue that complex soft interactions can actually be beneficial to the robot, and give rise to rich stimuli which can be used for the resolution of robot tasks. We further argue that the usefulness of these interactions depends on statistical regularities, or structure, that appear in the stimuli. To this end, robots should appropriately employ their morphology and their actions, to influence the system-environment interactions such that structure can arise in the stimuli. In this thesis we show that learning processes can be used to perform such a task. Following this rationale, this thesis proposes and supports the theory of Soft Morphological Computation (SoMComp), by which a soft robot should appropriately condition, or ‘affect’, the soft interactions to improve the quality of the physical stimuli arising from it. SoMComp is composed of four main principles, i.e.: Soft Proprioception, Soft Sensing, Soft Morphology and Soft Actuation. Each of these principles is explored in the context of haptic object recognition or object handling in soft robots. Finally, this thesis provides an overview of this research and its future directions.AHDB CP17

Bio-inspired soft robotic systems: Exploiting environmental interactions using embodied mechanics and sensory coordination

Despite the widespread development of highly intelligent robotic systems exhibiting great precision, reliability, and dexterity, robots remain incapable of performing basic manipulation tasks that humans take for granted. Manipulation in unstructured environments continues to be acknowledged as a significant challenge. Soft robotics, the use of less rigid materials in robots, has been proposed as one means of addressing these limitations. The technique enables more compliant interactions with the environment, allowing for increasingly adaptive behaviours better suited to more human-centric applications. Embodied intelligence is a biologically inspired concept in which intelligence is a function of the entire system, not only the controller or `brain'. This thesis focuses on the use of embodied intelligence for the development of soft robots, with a particular focus on how it can aid both perception and adaptability. Two main hypotheses are raised: first, that the mechanical design and fabrication of soft-rigid hybrid robots can enable increasingly environmentally adaptive behaviours, and second, that sensing materials and morphology can provide intelligence that assists perception through embodiment. A number of approaches and frameworks for the design and development of embodied systems are presented that address these hypotheses. It is shown how embodiment in soft sensor morphology can be used to perform localised processing and thereby distribute the intelligence over the body of a system. Specifically in soft robots, sensor morphology utilises the directional deformations created by interactions with the environment to aid in perception. Building on and formalising these ideas, a number of morphology-based frameworks are proposed for detecting different stimuli. The multifaceted role of materials in soft robots is demonstrated through the development of materials capable of both sensing and changes in material property. Such materials provide additional functionality beyond their integral scaffolding and static mechanical characteristics. In particular, an integrated material has been created exhibiting both sensing capabilities and also variable stiffness and `tack’ force, thereby enabling complex single-point grasping. To maximise the intelligence that can be gained through embodiment, a design approach to soft robots, `soft-rigid hybrid' design is introduced. This approach exploits passive behaviours and body dynamics to provide environmentally adaptive behaviours and sensing. It is leveraged by multi-material 3D printing techniques and novel approaches and frameworks for designing mechanical structures. The findings in this thesis demonstrate that an embodied approach to soft robotics provides capabilities and behaviours that are not currently otherwise achievable. Utilising the concept of `embodiment' results in softer robots with an embodied intelligence that aids perception and adaptive behaviours, and has the potential to bring the physical abilities of robots one step closer to those of animals and humans.EPSR

Life Support Baseline Values and Assumptions Document

The Baseline Values and Assumptions Document (BVAD) provides analysts, modelers, and other life support researchers with a common set of values and assumptions which can be used as a baseline in their studies. This baseline, in turn, provides a common point of origin from which many studies in the community may depart, making research results easier to compare and providing researchers with reasonable values to assume for areas outside their experience. This document identifies many specific physical quantities that define life support systems, serving as a general reference for spacecraft life support system technology developers

Wings in Orbit: Scientific and Engineering Legacies of the Space Shuttle, 1971-2010

The Space Shuttle is an engineering marvel perhaps only exceeded by the station itself. The shuttle was based on the technology of the 1960s and early 1970s. It had to overcome significant challenges to make it reusable. Perhaps the greatest challenges were the main engines and the Thermal Protection System. The program has seen terrible tragedy in its 3 decades of operation, yet it has also seen marvelous success. One of the most notable successes is the Hubble Space Telescope, a program that would have been a failure without the shuttle's capability to rendezvous, capture, repair, as well as upgrade. Now Hubble is a shining example of success admired by people around the world. As the program comes to a close, it is important to capture the legacy of the shuttle for future generations. That is what "Wings In Orbit" does for space fans, students, engineers, and scientists. This book, written by the men and women who made the program possible, will serve as an excellent reference for building future space vehicles. We are proud to have played a small part in making it happen. Our journey to document the scientific and engineering accomplishments of this magnificent winged vehicle began with an audacious proposal: to capture the passion of those who devoted their energies to its success while answering the question "What are the most significant accomplishments?" of the longestoperating human spaceflight program in our nation s history. This is intended to be an honest, accurate, and easily understandable account of the research and innovation accomplished during the era

Fruit Metabolism and Metabolomics

Over the past ten years, metabolomics strategies have allowed the relative or absolute quantitation of metabolite levels for the study of various biological questions in plant sciences. For fruit studies, in particular, they have participated in the identification of the genes underpinning fruit development and ripening. This book proposes examples of the current use of metabolomics studies of fruit for basic research or practical applications. It includes articles about several tropical and temperate fruit species. The studies concern fruit biochemical phenotyping, fruit metabolism during development and after harvest, including primary and specialized metabolisms, or bioactive compounds involved in fruit growth and environmental responses. The analytical strategies used are based mostly on liquid or gas chromatography coupled with mass spectrometry, but also on nuclear magnetic resonance and near-infrared spectroscopy. The effect of genotype, stages of development, or fruit tissue type on metabolomic profiles and corresponding metabolism regulations are addressed for fruit metabolism studies. The interest in combining other omics with metabolomics is also exemplified

Achieving robotically peeled lettuce

Robotic technologies are being increasingly applied to agriculture, in particular to harvesting. Some types of produce such as iceberg lettuce require additional processing after harvesting in order to satisfy the needs of the end-user or customer. Lettuce must have its outer leaves removed, a task that is currently performed manually. The leaf removal task represents a challenging vision and manipulation problem: the lettuce is in a random pose on a flat surface, from which the outermost leaves must be removed quickly and without causing damage. This letter presents a novel vision pipeline and suction removal system that enables robotic lettuce leaf removal. A suction nozzle and control procedure are used for the removal itself, relying on the orientation estimation and stem detection provided by the vision pipeline. To the best of the author's knowledge, this is the first robotic lettuce leaf peeling system

Achieving Robotically Peeled Lettuce

Robotic technologies are being increasingly applied to agriculture, in particular to harvesting. Some types of produce such as iceberg lettuce require additional processing after harvesting in order to satisfy the needs of the end-user or customer. Lettuce must have its outer leaves removed, a task that is currently performed manually. The leaf removal task represents a challenging vision and manipulation problem: the lettuce is in a random pose on a flat surface, from which the outermost leaves must be removed quickly and without causing damage. This letter presents a novel vision pipeline and suction removal system that enables robotic lettuce leaf removal. A suction nozzle and control procedure are used for the removal itself, relying on the orientation estimation and stem detection provided by the vision pipeline. To the best of the author's knowledge, this is the first robotic lettuce leaf peeling system

Achieving Robotically Peeled Lettuce

Robotic technologies are being increasingly applied to agriculture, in particular to harvesting. Some types of produce such as iceberg lettuce require additional processing after harvesting in order to satisfy the needs of the end-user or customer. Lettuce must have its outer leaves removed, a task that is currently performed manually. The leaf removal task represents a challenging vision and manipulation problem: the lettuce is in a random pose on a flat surface, from which the outermost leaves must be removed quickly and without causing damage. This letter presents a novel vision pipeline and suction removal system that enables robotic lettuce leaf removal. A suction nozzle and control procedure are used for the removal itself, relying on the orientation estimation and stem detection provided by the vision pipeline. To the best of the author's knowledge, this is the first robotic lettuce leaf peeling system

Achieving robotically peeled lettuce

Robotic technologies are being increasingly applied to agriculture, in particular to harvesting. Some types of produce such as iceberg lettuce require additional processing after harvesting in order to satisfy the needs of the end-user or customer. Lettuce must have its outer leaves removed, a task that is currently performed manually. The leaf removal task represents a challenging vision and manipulation problem: the lettuce is in a random pose on a flat surface, from which the outermost leaves must be removed quickly and without causing damage. This letter presents a novel vision pipeline and suction removal system that enables robotic lettuce leaf removal. A suction nozzle and control procedure are used for the removal itself, relying on the orientation estimation and stem detection provided by the vision pipeline. To the best of the author's knowledge, this is the first robotic lettuce leaf peeling system