A Dynamical System Approach for Resource-Constrained Mobile Robotics

The revolution of autonomous vehicles has led to the development of robots with abundant sensors, actuators with many degrees of freedom, high-performance computing capabilities, and high-speed communication devices. These robots use a large volume of information from sensors to solve diverse problems. However, this usually leads to a significant modeling burden as well as excessive cost and computational requirements. Furthermore, in some scenarios, sophisticated sensors may not work precisely, the real-time processing power of a robot may be inadequate, the communication among robots may be impeded by natural or adversarial conditions, or the actuation control in a robot may be insubstantial. In these cases, we have to rely on simple robots with limited sensing and actuation, minimal onboard processing, moderate communication, and insufficient memory capacity. This reality motivates us to model simple robots such as bouncing and underactuated robots making use of the dynamical system techniques. In this dissertation, we propose a four-pronged approach for solving tasks in resource-constrained scenarios: 1) Combinatorial filters for bouncing robot localization; 2) Bouncing robot navigation and coverage; 3) Stochastic multi-robot patrolling; and 4) Deployment and planning of underactuated aquatic robots. First, we present a global localization method for a bouncing robot equipped with only a clock and contact sensors. Space-efficient and finite automata-based combinatorial filters are synthesized to solve the localization task by determining the robot’s pose (position and orientation) in its environment. Second, we propose a solution for navigation and coverage tasks using single or multiple bouncing robots. The proposed solution finds a navigation plan for a single bouncing robot from the robot’s initial pose to its goal pose with limited sensing. Probabilistic paths from several policies of the robot are combined artfully so that the actual coverage distribution can become as close as possible to a target coverage distribution. A joint trajectory for multiple bouncing robots to visit all the locations of an environment is incrementally generated. Third, a scalable method is proposed to find stochastic strategies for multi-robot patrolling under an adversarial and communication-constrained environment. Then, we evaluate the vulnerability of our patrolling policies by finding the probability of capturing an adversary for a location in our proposed patrolling scenarios. Finally, a data-driven deployment and planning approach is presented for the underactuated aquatic robots called drifters that creates the generalized flow pattern of the water, develops a Markov-chain based motion model, and studies the long- term behavior of a marine environment from a flow point-of-view. In a broad summary, our dynamical system approach is a unique solution to typical robotic tasks and opens a new paradigm for the modeling of simple robotics system

Automated Road Lane Detection for Intelligent Vehicles

Automated road lane detection is the crucial part of vision-based driver assistance system of intelligent vehicles. This driver assistance system reduces the road accidents, enhances safety and improves the traffic conditions. In this paper, we present an algorithm for detecting marks of road lane and road boundary with a view to the smart navigation of intelligent vehicles. Initially, it converts the RGB road scene image into gray image and employs the flood-fill algorithm to label the connected components of that gray image. Afterwards, the largest connected component which is the road region is extracted from the labeled image using maximum width and no. of pixels. Eventually, the outside region is subtracted and the marks or road lane and road boundary are extracted from connected components. The experimental results show the effectiveness of the proposed algorithm on both straight and slightly curved road scene images under different day light conditions and the presence of shadows on the roads

Multi-Robot Coverage and Persistent Monitoring in Sensing-Constrained Environments

This article examines the problems of multi-robot coverage and persistent monitoring of regions of interest with limited sensing robots. A group of robots, each equipped with only contact sensors and a clock, execute a simple trajectory by repeatedly moving straight and then bouncing at perimeter boundaries by rotating in place. We introduce an approach by finding a joint trajectory for multiple robots to cover a given environment and generating cycles for the robots to persistently monitor the target regions in the environment. From a given initial configuration, our approach iteratively finds the joint trajectory of all the robots that covers the entire environment. Our approach also computes periodic trajectories of all the robots for monitoring of some regions, where trajectories overlap but do not involve robot-robot collisions. We present experimental results from multiple simulations and physical experiments demonstrating the practical utility of our approach

Cascade of diabetes care in Bangladesh, Bhutan and Nepal: identifying gaps in the screening, diagnosis, treatment and control continuum

Abstract Diabetes has become a major cause of morbidity and mortality in South Asia. Using the data from the three STEPwise approach to Surveillance (STEPS) surveys conducted in Bangladesh, Bhutan, and Nepal during 2018–2019, this study tried to quantify the gaps in diabetes screening, awareness, treatment, and control in these three South Asian countries. Diabetes care cascade was constructed by decomposing the population with diabetes (diabetes prevalence) in each country into five mutually exclusive and exhaustive categories: (1) unscreened and undiagnosed, (2) screened but undiagnosed, (3) diagnosed but untreated, (4) treated but uncontrolled, (5) treated and controlled. In Bangladesh, Bhutan, and Nepal, among the participants with diabetes, 14.7%, 35.7%, and 4.9% of the participants were treated and controlled, suggesting that 85.3%, 64.3%, and 95.1% of the diabetic population had unmet need for care, respectively. Multivariable logistic regression models were used to explore factors associated with awareness of the diabetes diagnosis. Common influencing factors for awareness of the diabetes diagnosis for Bangladesh and Nepal were living in urban areas [Bangladesh-adjusted odd ratio (AOR):2.1; confidence interval (CI):1.2, 3.6, Nepal-AOR:6.2; CI:1.9, 19.9]

Towards Sustainable and Livable Cities: Leveraging Remote Sensing, Machine Learning, and Geo-Information Modelling to Explore and Predict Thermal Field Variance in Response to Urban Growth

Urbanization-led changes in land use land cover (LULC), resulting in an increased impervious surface, significantly deteriorate urban meteorological conditions compromising long-term sustainability. In this context, we leverage machine learning, spatial modelling, and cloud computing to explore and predict the changing patterns in urban growth and associated thermal characteristics in Bahawalpur, Pakistan. Using multi-source earth observations (1990–2020), the urban thermal field variance index (UTFVI) is estimated to evaluate the urban heat island effect quantitatively. From 1990 to 2020, the urban area increased by ~90% at the expense of vegetation and barren land, which will further grow by 2050 (50%), as determined by the artificial neural network-based prediction. The land surface temperature in the summer and winter seasons has experienced an increase of 0.88 °C and ~5 °C, respectively. While there exists spatial heterogeneity in the UTFVI 1990–2020, the city is expected to experience a ~140% increase in areas with severe UTFVI in response to predicted LULC change by 2050. The study provides essential information on LULC change and UTFVI and puts forth useful insights to advance our understanding of the urban climate, which can progressively help in designing more livable and sustainable cities in the face of environmental changes

Spectrum of intradialytic complications during hemodialysis and its management: A single-center experience

Hemodialysis (HD) is one of the important modalities of renal replacement therapy in acute renal failure (ARF) as well as chronic renal failure (CRF). This study was performed to evaluate the various intradialytic complications that occur during HD and their management. This is a retrospective study performed in patients who underwent conventional HD during the period of 1 January 2000 to 31 December 2011 at our center. Clinical details, various complications faced and their management were retrieved from dialysis case sheets. A total of 2325 patients of renal failure (790 ARF and 1535 CRF patients) were assessed for the intradialytic complications of HD. During the study period, there were 12,785 bicarbonate dialyses performed on these patients. In the ARF patients, the common intradialytic complications were: Hypotension, seen in 1296 sessions (30.4%), nausea and vomiting seen in 1125 sessions (26.4%), fever and chills seen in 818 sessions (19.2%), headache seen in 665 sessions (15.6%), cramps seen in 85 sessions (2.0%), chest pain and back pain seen in 82 sessions (1.92%), hypoglycemia seen in 77 sessions (1.8%), first-use syndrome seen in 72 sessions (1.7%) and femoral hematoma seen in 31 sessions (0.73%). In the CRF group, common complications were hypotension in 2230 sessions (26.1%), nausea and vomiting in 1211 sessions (14.2%), fever and chills in 1228 sessions (14.4%), chest pain and back pain in 1108 cases (13.0%), hypertension in 886 sessions (10.4%), headache in 886 sessions (10.4%), cramps in 256 sessions (3.0%), hematoma in 55 sessions (0.64%), intracerebral hemorrhage in three sessions (0.03%) and catheter tip migration in three sessions (0.03%). There is a need for special attention for the diagnosis and management of intradialytic complications of HD because such complications could be managed successfully without the need for termination of the dialysis procedure

Disseminated Histoplasmosis presenting as oropharyngeal mass lesion

A 62 year old man from Silchar in North East India presented with complaints of painful swallowing, hoarseness, fever, anorexia and weight loss. Oropharyngeal examination revealed reddish ulcero-nodular lesion involving left tonsillar area and base of tongue which was clinically suspicious of malignancy. Radiological examination revealed involvement of bilateral adrenals by a mass. The biopsy of the oropharyngeal lesion showed many fungal spores morphologically favoring Histoplasmosis. Treatment with Amphotericin B followed by Itraconazole resulted recovery of lesions. Keywords: Disseminated histoplasmosis, Oropharynx, Mass lesio