Airborne chemical sensing with mobile robots

Airborne chemical sensing with mobile robots has been an active research areasince the beginning of the 1990s. This article presents a review of research work in this field,including gas distribution mapping, trail guidance, and the different subtasks of gas sourcelocalisation. Due to the difficulty of modelling gas distribution in a real world environmentwith currently available simulation techniques, we focus largely on experimental work and donot consider publications that are purely based on simulations

MultiBac: expanding the research toolbox for multiprotein complexes

This article is made available for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.Protein complexes composed of many subunits carry out most essential processes in cells and, therefore, have become the focus of intense research. However, deciphering the structure and function of these multiprotein assemblies imposes the challenging task of producing them in sufficient quality and quantity. To overcome this bottleneck, powerful recombinant expression technologies are being developed. In this review, we describe the use of one of these technologies, MultiBac, a baculovirus expression vector system that is particularly tailored for the production of eukaryotic multiprotein complexes. Among other applications, MultiBac has been used to produce many important proteins and their complexes for their structural characterization, revealing fundamental cellular mechanisms

Biological Organisms as End Effectors

In robotics, an end effector is a device at the end of a robotic arm designed to interact with the environment. Effectively, it serves as the hand of the robot, carrying out tasks on behalf of humans. But could we turn this concept on its head and consider using living organisms themselves as end-effectors? This paper introduces a novel idea of using whole living organisms as end effectors for robotics. We showcase this by demonstrating that pill bugs and chitons -- types of small, harmless creatures -- can be utilized as functional grippers. Crucially, this method does not harm these creatures, enabling their release back into nature after use. How this concept may be expanded to other organisms and applications is also discussed.Comment: 11 pages, 8 figure

An artificial moth: Chemical source localization using a robot based neuronal model of moth optomotor anemotactic search

Robots have been used to model nature, while nature in turn can contribute to the real-world artifacts we construct. One particular domain of interest is chemical search where a number of efforts are underway to construct mobile chemical search and localization systems. We report on a project that aims at constructing such a system based on our understanding of the pheromone communication system of the moth. Based on an overview of the peripheral processing of chemical cues by the moth and its role in the organization of behavior we emphasize the multimodal aspects of chemical search, i.e. optomotor anemotactic chemical search. We present a model of this behavior that we test in combination with a novel thin metal oxide sensor and custom build mobile robots. We show that the sensor is able to detect the odor cue, ethanol, under varying flow conditions. Subsequently we show that the standard model of insect chemical search, consisting of a surge and cast phases, provides for robust search and localization performance. The same holds when it is augmented with an optomotor collision avoidance model based on the Lobula Giant Movement Detector (LGMD) neuron of the locust. We compare our results to others who have used the moth as inspiration for the construction of odor robot

Reactive localisation of an odour source by a learning mobile robot

The goal of this work was to enable a mobile robot to navigate autonomously towards a stationary odour source with the help of a sense of smell. Two electronic noses, each containing a set of gas sensors, mounted on top of a Koala mobile robot were used for detection of the odour. The sensing strategy used for data collection was investigated in order to reduce the influence of air turbulences on the sample handling process. Then a multi-layer artificial neural network was used to learn both the direction to the source and the required turning speed of the robot. An experimental validation was carried out to evaluate the performance of the complete system

Recent Advances and Current Developments in Tissue Scaffolding

A bio-scaffold can be broadly termed as a structure used to substitute an organ either permanently or temporarily to restore functionality. The material that can be used varies with the application intended. Tissue engineering is one such application demanding certain requirements to be met before it is applied. One of the applications in tissue engineering is the tissue scaffold, which provides either a permanent or temporary support to the damaged tissues/organ until the functionalities are restored. A biomaterial can exhibit specific interactions with cells that will lead to stereotyped responses. The use of a particular material and morphology depends on various factors such as osteoinduction, osteoconduction, angiogenesis, growth rates of cells and degradation rate of the material in case of temporary scaffolds, etc. The current work reviews the state of art in tissue scaffolds and focuses on permanent scaffold materials and applications with a brief overview of temporary scaffold materials and their disadvantages

Adaptive Bayesian sensor motion planning for hazardous source term reconstruction

There has been a strong interest in emergency planning in response to an attack or accidental release of harmful chemical, biological, radiological or nuclear substances. Under such circumstances, it is of paramount importance to determine the location and release rate of the hazardous source to forecast the future harm it may cause and employ methods to minimize the disturbance. In this paper, a sensor data collection strategy is proposed whereby an autonomous mobile sensor is guided to address such a problem with a high degree of accuracy and in a short amount of time. First, the parameters of the release source are estimated using the Markov chain Monte Carlo sampling approach. The most informative manoeuvre from the set of possible choices is then selected using the concept of maximum entropy sampling. Numerical simulations demonstrate the superior performance of the proposed algorithm compared to traditional approaches in terms of estimation accuracy and the number of measurements required