50 research outputs found
Efficient Remote Gas Inspection with an Autonomous Mobile Robot
No full textHuman-caused greenhouse gas emissions are one of the major sources of global warming, which is threatening to reach a tipping point. Inspection systems that can provide direct information about critical factors causing global warming, such as systems for gas detection and location of gas sources, are urgently needed to analyze the fugitive emissions and take necessary actions. This thesis presents an autonomous robotic system capable of performing efficient exploration by selecting informative sampling positions for gas detection and gas distribution mapping – the Autonomous Remote Methane Explorer (ARMEx). In the design choice of ARMEx, a ground robot carries a spectroscopybased remote gas sensor, such as a Remote Methane Leak Detector (RMLD), that collects integral gas measurements along up to 30 m long optical-beams. The sensor is actuated to sample a large area inside an adjustable field of view, and with the mobility of the robot, adaptive sampling for high spatial resolution in the areas of interest is made possible to inspect large environments. In a typical gas sampling mission, the robot needs to localize itself and plan a traveling path to visit different locations in the area, which is a largely solved problem. However, the state-of-the-art prior to this thesis fell short of providing the capability to select informative sampling positions autonomously. This thesis introduces efficient measurement strategies to bring autonomy to mobile remote gas sensing. The strategies are based on sensor planning algorithms that minimize the number of measurements and distance traveled while optimizing the inspection criteria: full sensing coverage of the area for gas detection, and suitably overlapping sensing coverage of different viewpoints around areas of interest for gas distribution mapping. A prototype implementation of ARMEx was deployed in a large, real-world environment where inspection missions performed by the autonomous system were compared with runs teleoperated by human experts. In six experimental trials, the autonomous system created better gas maps, located more gas sources correctly, and provided better sensing coverage with fewer sensing positions than human experts
Global coverage measurement planning strategies for mobile robots equipped with a remote gas sensor
No full textThe problem of gas detection is relevant to many real-world applications, such as leak detection in industrial settings and landfill monitoring. In this paper, we address the problem of gas detection in large areas with a mobile robotic platform equipped with a remote gas sensor. We propose an algorithm that leverages a novel method based on convex relaxation for quickly solving sensor placement problems, and for generating an efficient exploration plan for the robot. To demonstrate the applicability of our method to real-world environments, we performed a large number of experimental trials, both on randomly generated maps and on the map of a real environment. Our approach proves to be highly efficient in terms of computational requirements and to provide nearly-optimal solutions
Nonlinear System Identification Using Neural Network
No full textMagneto-rheological damper is a nonlinear system. In this case study, system has been identified using Neural Network tool. Optimization between number of neurons in the hidden layer and number of epochs has been achieved and discussed by using multilayer perceptron Neural Network
Sniffing out fugitive methane emissions : autonomous remote gas inspection with a mobile robot
No full textAir pollution causes millions of premature deaths every year, and fugitive emissions of, e.g., methane are major causes of global warming. Correspondingly, air pollution monitoring systems are urgently needed. Mobile, autonomous monitoring can provide adaptive and higher spatial resolution compared with traditional monitoring stations and allows fast deployment and operation in adverse environments. We present a mobile robot solution for autonomous gas detection and gas distribution mapping using remote gas sensing. Our ‘‘Autonomous Remote Methane Explorer’’ (ARMEx) is equipped with an actuated spectroscopy-based remote gas sensor, which collects integral gas measurements along up to 30 m long optical beams. State-of-the-art 3D mapping and robot localization allow the precise location of the optical beams to be determined, which then facilitates gas tomography (tomographic reconstruction of local gas distributions from sets of integral gas measurements). To autonomously obtain informative sampling strategies for gas tomography, we reduce the search space for gas inspection missions by defining a sweep of the remote gas sensor over a selectable field of view as a sensing configuration. We describe two different ways to find sequences of sensing configurations that optimize the criteria for gas detection and gas distribution mapping while minimizing the number of measurements and distance traveled. We evaluated anARMExprototype deployed in a large, challenging indoor environment with eight gas sources. In comparison with human experts teleoperating the platform from a distant building, the autonomous strategy produced better gas maps with a lower number of sensing configurations and a slightly longer route.</p
A case of otogenic tetanus.
No full textThe authors are presenting our experience of managing an interesting case of a 12-year-old girl who presented to our clinic with otorrhea for 3 months and trismus for 1 week. Examination showed bilateral ear discharge with central perforations in tympanic membranes, palatal paralysis and trismus. Systemic examination revealed only mild stiffness of hand muscles. CT-scan head and neck was done to look for intracranial complications of otitis media. However, it revealed only decreased pneumatisation of mastoid cells. She was admitted in the hospital and started on intravenous and local antibiotics after sending ear swab and blood cultures. But she showed no improvement in 48 h. So on the clinical suspicion (trismus and stiffness of hands) remote possibility of otogenic tetanus was considered and she was given tetanus toxoid and immunoglobulins. She gradually showed improvement in her symptoms. Thereafter, culture from ear discharge was also reported positive for Clostridium tetani
The Right Direction to Smell : Efficient Sensor Planning Strategies for Robot Assisted Gas Tomography
No full textCreating an accurate model of gas emissions is an important task in monitoring and surveillance applications. A promising solution for a range of real-world applications are gas-sensitive mobile robots with spectroscopy-based remote sensors that are used to create a tomographic reconstruction of the gas distribution. The quality of these reconstructions depends crucially on the chosen sensing geometry. In this paper we address the problem of sensor planning by investigating sensing geometries that minimize reconstruction errors, and then formulate an optimization algorithm that chooses sensing configurations accordingly. The algorithm decouples sensor planning for single high concentration regions (hotspots) and subsequently fuses the individual solutions to a global solution consisting of sensing poses and the shortest path between them. The proposed algorithm compares favorably to a template matching technique in a simple simulation and in a real-world experiment. In the latter, we also compare the proposed sensor planning strategy to the sensing strategy of a human expert and find indications that the quality of the reconstructed map is higher with the proposed algorithm
A comparison of search-based planners for a legged robot
No full textPath planning for multi-DoF legged robots is achallenging task due to the high dimensionality and complexityof the planning space. We present our first attempt to builda path planning framework for the hydraulic quadruped -HyQ. Our approach adopts a similar strategy to [1], whereplanning is divided into a task-space and a joint-space part.The task-space planner finds a path for the center of gravity(COG) of the robot, while then the footstep planner generates theappropriate footholds under reachability and stability criteria.Next the joint-space planner translates the task-space COGtrajectories into robot joint angles. We present a comparisonof a set of search-based planning algorithms; Dijkstra, A* andARA*, and evaluate these over a set of given terrains and anumber of varying start and end points. All test runs supportthat our approach is a simple yet robust solution. We reportcomparisons in path length, computation time, and path cost,between the aforementioned planning algorithms
