Hand-eye calibration enables proper perception of the environment in which a vision guided robot operates. Additionally, it enables the mapping of the scene in the robots frame. Proper hand-eye calibration is crucial when sub-millimetre perceptual accuracy is needed. For example, in robot assisted surgery, a poorly calibrated robot would cause damage to surrounding vital tissues and organs, endangering the life of a patient. A lot of research has gone into ways of accurately calibrating the hand-eye system of a robot with different levels of success, challenges, resource requirements and complexities. As such, academics and industrial practitioners are faced with the challenge of choosing which algorithm meets the implementation requirements based on the identified constraints. This review aims to give a general overview of the strengths and weaknesses of different hand-eye calibration algorithms available to academics and industrial practitioners to make an informed design decision, as well as incite possible areas of research based on the identified challenges. We also discuss different calibration targets, which is an important part of the calibration process that is often overlooked in the design process.

Nucleic acid-based chemistry is a strong candidate framework for the construction of future synthetic biomolecular control circuits. Previous work has demonstrated the capacity of circuits based on DNA strand displacement reactions to implement digital and analogue signal processing in vivo, including in mammalian cells. To date, however, feedback control system designs attempted within this framework have been restricted to extremely simple proportional or proportional-integral controller architectures. In this work, we significantly extend the potential complexity of such controllers by showing how time-delays, numerical differentiation (to allow PID control), and state feedback may be implemented via chemical reaction network-based designs. Our controllers are implemented and tested using VisualDSD, a rapid-prototyping tool that allows precise analysis of computational devices implemented using nucleic acids, via both deterministic and stochastic simulations of the DNA strand displacement reactions.

A wide range of organisms features molecular machines, circadian clocks, which generate endogenous oscillations with ~24 h periodicity and thereby synchronize biological processes to diurnal environmental fluctuations. Recently, it has become clear that plants harbor more complex gene regulatory circuits within the core circadian clocks than other organisms, inspiring a fundamental question: are all these regulatory interactions between clock genes equally crucial for the establishment and maintenance of circadian rhythms? Our mechanistic simulation for Arabidopsis thaliana demonstrates that at least half of the total regulatory interactions must be present to express the circadian molecular profiles observed in wild-type plants. A set of those essential interactions is called herein a kernel of the circadian system. The kernel structure unbiasedly reveals four interlocked negative feedback loops contributing to circadian rhythms, and three feedback loops among them drive the autonomous oscillation itself. Strikingly, the kernel structure, as well as the whole clock circuitry, is overwhelmingly composed of inhibitory, rather than activating, interactions between genes. We found that this tendency underlies plant circadian molecular profiles which often exhibit sharply-shaped, cuspidate waveforms. Through the generation of these cuspidate profiles, inhibitory interactions may facilitate the global coordination of temporally-distant clock events that are markedly peaked at very specific times of day. Our systematic approach resulting in experimentally-testable predictions provides insights into a design principle of biological clockwork, with implications for synthetic biology. Sleep/wake cycles in animals exemplify daily biological rhythms driven by internal molecular clocks, circadian clocks, which are important for plant life as well. The plant circadian clock is highly complex, eluding our understanding of its design principle. Based on the computational simulation of Arabidopsis thaliana, we successfully identified a kernel of the plant circadian system, the critical genetic circuitry for clock function. The kernel integrates four major negative feedback loops that process molecular circadian oscillations. Surprisingly, the plant clock circuitry was found to be overwhelmingly composed of inhibitory, rather than activating, interactions among genes. This fact underlies plant circadian molecular profiles to often exhibit sharply-shaped, cuspidate waveforms, which indicate clock events that are markedly peaked at very specific times of day. Our work presents experimentally-testable predictions, with implications for synthetic biology.

The byssal threads of the fan shell Atrina pectinata are non-living functional materials intimately associated with living tissue, which provide an intriguing paradigm of bionic interface for robust load-bearing device. An interfacial load-bearing protein (A. pectinata foot protein-1, apfp-1) with L-3,4-dihydroxyphenylalanine (DOPA)-containing and mannose-binding domains has been characterized from Atrina’s foot. apfp-1 was localized at the interface between stiff byssus and the soft tissue by immunochemical staining and confocal Raman imaging, implying that apfp-1 is an interfacial linker between the byssus and soft tissue, that is, the DOPA-containing domain interacts with itself and other byssal proteins via Fe3⁺–DOPA complexes, and the mannose-binding domain interacts with the soft tissue and cell membranes. Both DOPA- and sugar-mediated bindings are reversible and robust under wet conditions. This work shows the combination of DOPA and sugar chemistry at asymmetric interfaces is unprecedented and highly relevant to bionic interface design for tissue engineering and bionic devices.

Hand-eye calibration is an important step in controlling a vision-guided robot in applications like part assembly, bin picking and inspection operations etc. Many methods for estimating hand-eye transformations have been proposed in literature with varying degrees of complexity and accuracy. However, the success of a vision-guided application is highly impacted by the accuracy the hand-eye calibration of the vision system with the robot. The level of this accuracy depends on several factors such as rotation and translation noise, rotation and translation motion range that must be considered during calibration. Previous studies and benchmarking of the proposed algorithms have largely been focused on the combined effect of rotation and translation noise. This study provides insight on the impact of rotation and translation noise acting in isolation on the hand-eye calibration accuracy. This deviates from the most common method of assessing hand-eye calibration accuracy based on pose noise (combined rotation and translation noise). We also evaluated the impact of the robot motion range used during the hand-eye calibration operation which is rarely considered. We provide quantitative evaluation of our study using six commonly used algorithms from an implementation perspective. We comparatively analyse the performance of these algorithms through simulation case studies and experimental validation using the Universal Robot’s UR5e physical robots. Our results show that these different algorithms perform differently when the noise conditions vary rather than following a general trend. For example, the simultaneous methods are more resistant to rotation noise, whereas the separate methods are better at dealing with translation noise. Additionally, while increasing the robot rotation motion span during calibration enhances the accuracy of the separate methods, it has a negative effect on the simultaneous methods. Conversely, increasing the translation motion range improves the accuracy of simultaneous methods but degrades the accuracy of the separate methods. These findings suggest that those conditions should be considered when benchmarking algorithms or performing a calibration process for enhanced accuracy.

Recent progresses in data-driven analysis methods, including network-based approaches, are revolutionizing many classical disciplines. These techniques can also be applied to food and nutrition, which must be studied to design healthy diets. Using nutritional information from over 1,000 raw foods, we systematically evaluated the nutrient composition of each food in regards to satisfying daily nutritional requirements. The nutrient balance of a food was quantified and termed nutritional fitness; this measure was based on the food’s frequency of occurrence in nutritionally adequate food combinations. Nutritional fitness offers a way to prioritize recommendable foods within a global network of foods, in which foods are connected based on the similarities of their nutrient compositions. We identified a number of key nutrients, such as choline and α-linolenic acid, whose levels in foods can critically affect the nutritional fitness of the foods. Analogously, pairs of nutrients can have the same effect. In fact, two nutrients can synergistically affect the nutritional fitness, although the individual nutrients alone may not have an impact. This result, involving the tendency among nutrients to exhibit correlations in their abundances across foods, implies a hidden layer of complexity when exploring for foods whose balance of nutrients within pairs holistically helps meet nutritional requirements. Interestingly, foods with high nutritional fitness successfully maintain this nutrient balance. This effect expands our scope to a diverse repertoire of nutrient-nutrient correlations, which are integrated under a common network framework that yields unexpected yet coherent associations between nutrients. Our nutrient-profiling approach combined with a network-based analysis provides a more unbiased, global view of the relationships between foods and nutrients, and can be extended towards nutritional policies, food marketing, and personalized nutrition.