45 research outputs found
Bacterium-inspired Robots for Environmental Monitoring
Locating gradient sources and tracking them over time has important applications to environmental monitoring and studies of the ecosystem. We present an approach, inspired by bacterial chemotaxis, for robots to navigate to sources using gradient measurements and a simple actuation strategy (biasing a random walk). Extensive simulations show the efficacy of the approach in varied conditions including multiple sources, dissipative sources, and noisy sensors and actuators. We also show how such an approach could be used for boundary finding. We validate our approach by testing it on a small robot (the robomote) in a phototaxis experiment. A comparison of our approach with gradient descent shows that while gradient descent is faster, our approach is better suited for boundary coverage, and performs better in the presence of multiple and dissipative sources
AMBROSia: An Autonomous Model-Based Reactive Observing System
Observing systems facilitate scientific studies by instrumenting the real world and collecting corresponding measurements, with the aim of detecting and tracking phenomena of interest. Our AMBROSia project focuses on a class of observing systems which are embedded into the environment, consist of stationary and mobile sensors, and react to collected observations by reconfiguring the system and adapting which observations are collected next. In this paper, we report on recent research directions and corresponding results in the context of AMBROSia
Association of acute toxic encephalopathy with litchi consumption in an outbreak in Muzaffarpur, India, 2014: a case-control study
Background Outbreaks of unexplained illness frequently remain under-investigated. In India, outbreaks of an acute
neurological illness with high mortality among children occur annually in Muzaffarpur, the country’s largest litchi
cultivation region. In 2014, we aimed to investigate the cause and risk factors for this illness.
Methods In this hospital-based surveillance and nested age-matched case-control study, we did laboratory
investigations to assess potential infectious and non-infectious causes of this acute neurological illness. Cases were
children aged 15 years or younger who were admitted to two hospitals in Muzaffarpur with new-onset seizures or
altered sensorium. Age-matched controls were residents of Muzaffarpur who were admitted to the same two hospitals
for a non-neurologic illness within seven days of the date of admission of the case. Clinical specimens (blood,
cerebrospinal fluid, and urine) and environmental specimens (litchis) were tested for evidence of infectious
pathogens, pesticides, toxic metals, and other non-infectious causes, including presence of hypoglycin A or
methylenecyclopropylglycine (MCPG), naturally-occurring fruit-based toxins that cause hypoglycaemia and metabolic
derangement. Matched and unmatched (controlling for age) bivariate analyses were done and risk factors for illness
were expressed as matched odds ratios and odds ratios (unmatched analyses).
Findings Between May 26, and July 17, 2014, 390 patients meeting the case definition were admitted to the two referral
hospitals in Muzaffarpur, of whom 122 (31%) died. On admission, 204 (62%) of 327 had blood glucose concentration
of 70 mg/dL or less. 104 cases were compared with 104 age-matched hospital controls. Litchi consumption (matched
odds ratio [mOR] 9·6 [95% CI 3·6 – 24]) and absence of an evening meal (2·2 [1·2–4·3]) in the 24 h preceding illness
onset were associated with illness. The absence of an evening meal significantly modified the effect of eating litchis
on illness (odds ratio [OR] 7·8 [95% CI 3·3–18·8], without evening meal; OR 3·6 [1·1–11·1] with an evening meal).
Tests for infectious agents and pesticides were negative. Metabolites of hypoglycin A, MCPG, or both were detected in
48 [66%] of 73 urine specimens from case-patients and none from 15 controls; 72 (90%) of 80 case-patient specimens
had abnormal plasma acylcarnitine profiles, consistent with severe disruption of fatty acid metabolism. In 36 litchi
arils tested from Muzaffarpur, hypoglycin A concentrations ranged from 12·4 μg/g to 152·0 μg/g and MCPG ranged
from 44·9 μg/g to 220·0 μg/g.
Interpretation Our investigation suggests an outbreak of acute encephalopathy in Muzaffarpur associated with both
hypoglycin A and MCPG toxicity. To prevent illness and reduce mortality in the region, we recommended minimising
litchi consumption, ensuring receipt of an evening meal and implementing rapid glucose correction for suspected
illness. A comprehensive investigative approach in Muzaffarpur led to timely public health recommendations,
underscoring the importance of using systematic methods in other unexplained illness outbreaks
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Bacterium-Inspired Robots for Environmental Monitoring
Locating gradient sources and tracking them over time has important applications to environmental monitoring and studies of the ecosystem. We present an approach, inspired by bacterial chemotaxis, for robots to navigate to sources using gradient measurements and a simple actuation strategy (biasing a random walk). Extensive simulations show the efficacy of the approach in varied conditions including multiple sources, dissipative sources, and noisy sensors and actuators. We also show how such an approach could be used for boundary finding. We validate our approach by testing it on a small robot (the robomote) in a phototaxis experiment. A comparison of our approach with gradient descent shows that while gradient descent is faster, our approach is better suited for boundary coverage, and performs better in the presence of multiple and dissipative sources
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Bacteria-Inspired Motion Strategies for Robotic Sensor Networks
The poster presents a very simple approach for source and boundary detection using biased random walks (inspired from bacterial motion) which could be a novel strategy for robotic sensor network problems
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Bacterium-inspired Robots for Environmental Monitoring
This paper presents an approach, inspired by bacterial chemotaxis, for robots to navigate to sources using gradient measurements and a simple actuation strategy (biasing a random walk). To appear in IEEE International Conference on Robotics and Automation, Apr 2004
Ad-Hoc Localization Using Ranging and Sectoring
Ad-hoc localization systems enable nodes in a sensor network to fix their positions in a global coordinate system using a relatively small number of anchor nodes that know their position through external means (e.g., GPS). Because location information provides context to sensed data, such systems are a critical component of many sensor networks and have therefore received a fair amount of recent attention in the sensor networks literature. The efficacy of these systems is a function of the density of deployment and of anchor nodes, as well as the error in distance estimation (ranging) between nodes
Bacterium-inspired robots for environmental monitoring
Abstract — Locating gradient sources and tracking them over time has important applications to environmental monitoring and studies of the ecosystem. We present an approach, inspired by bacterial chemotaxis, for robots to navigate to sources using gradient measurements and a simple actuation strategy (biasing a random walk). Extensive simulations show the efficacy of the approach in varied conditions including multiple sources, dissipative sources, and noisy sensors and actuators. We also show how such an approach could be used for boundary finding. We validate our approach by testing it on a small robot (the robomote) in a phototaxis experiment. A comparison of our approach with gradient descent shows that while gradient descent is faster, our approach is better suited for boundary coverage, and performs better in the presence of multiple and dissipative sources. I
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Bacterial Navigation and Applications to Sensing in Marine Environments
A variety of naturally-occurring and introduced microorganisms adversely impact marine ecosystems. They can affect human health, fisheries and even tourism. However, conditions under which aquatic microorganisms develop are not well understood, and methods for detecting microorganisms are too slow and complex for timely intervention. With the development of technology, sensor networks provide a method to monitor the microorganisms in real time and solve the problem. The ability to autonomously detect, locate and track such phenomena (the source of the induced gradient) would give scientists a tool to monitor and study ecosystems at an unprecedented level of detail. We are in particular motivated by the research goal to track the brown-tide algal blooms in nature and follow their migration over time. We plan to locate these algae and measure their concentrations using a chlorophyll sensor