Sensing and control for a small-size helicopter

This paper details the progress to date, toward developing a small autonomous helicopter. We describe system architecture, avionics, visual state estimation, custom IMU design, aircraft modelling, as well as various linear and neuro/fuzzy control algorithms. Experimental results are presented for state estimation using fused stereo vision and IMU data, heading control, and attitude control. FAM attitude and velocity controllers have been shown to be effective in simulation.

Coordination of UAV path planning in 2D and 3D in environmental/bio sensing applications

This paper is concerned with the optimal path planning and initialization interval of one or two UAVs in presence of a constant wind. The method compares previous literature results on synchronization of UAVs along convex curves, path planning and sampling in 2D and extends it to 3D. This method can be applied to observe gas/particle emissions inside a control volume during sampling loops. The flight pattern is composed of two phases: a start-up interval and a sampling interval which is represented by a semi-circular path. The methods were tested in four complex model test cases in 2D and 3D as well as one simulated real world scenario in 2D and one in 3D.

Hydrogen gas sensing performance of Pt/SnO2 nanowires/SiC MOS devices

This paper presents material and gas sensing properties of Pt/SnO2 nanowires/SiC metal oxide semiconductor devices towards hydrogen. The SnO2 nanowires were deposited onto the SiC substrates by vapour-liquid-solid growth mechanism. The material properties of the sensors were investigated using scanning electron microscopy, transmission electron microscopy and X-ray photoelectron spectroscopy. The current-voltage characteristics have been analysed. The effective change in the barrier height for 1% hydrogen was found to be 142.91 meV. The dynamic response of the sensors towards hydrogen at different temperatures has also been studied. At 530°C, voltage shift of 310 mV for 1% hydrogen was observed.

A comparison study on hydrogen sensing performance of Pt/MoO3 nanoplatelets coated with a thin layer of Ta2O5 or La2O3

In this work, we investigate how hydrogen sensing performance of thermally evaporated MoO3 nanoplatelets can be further improved by RF sputtering a thin layer of tantalum oxide (Ta2O5) or lanthanum oxide (La2O3). We show that dissociated hydrogen atoms cause the thin film layer to be polarised, inducing a measurable potential difference greater than that as reported previously. We attribute these observations to the presence of numerous traps in the thin layer; their states allow a stronger trapping of charge at the Pt-thin film oxide interface as compared to the MoO3 sensors without the coating. Under exposure to H2 (10 000 ppm) the maximum change in dielectric constant of 45.6 (at 260 °C) for the Ta2O5/MoO3 nanoplatelets and 31.6 (at 220 °C) for La2O3/MoO3 nanoplatelets. Subsequently, the maximum sensitivity for the Ta2O5/MoO3 is 16.87 (at 260 °C) and La2O3/MoO3 is 7.52 (at 300 °C).

Pt/ZnO/SiC thin film for hydrogen gas sensing

Zinc oxide (ZnO) is one of the most promising electronic and photonic materials to date. In this work, we present an enhanced ZnO Schottky gas sensor deposited on SiC substrates in comparison to those reported previously in literature. The performance of ZnO/SiC based Schottky thin film gas sensors produced a forward lateral voltage shift of 12.99mV and 111.87mV in response to concentrations of hydrogen gas at 0.06% and 1% in air at optimum temperature of 330 ºC. The maximum change in barrier height was calculated as 37.9 meV for 1% H2 sensing operation at the optimum temperature.

Pt/anodized TiO2/SiC-based MOS device for hydrocarbon sensing

Pt/anodized TiO2/SiC based metal-oxide-semiconductor (MOS) devices were fabricated and characterized for their sensitivity towards propene (C3H6). Titanium (Ti) thin films were deposited onto the SiC substrates using a filtered cathodic vacuum arc (FCVA) method. Fluoride ions containing neutral electrolyte (0.5 wt% NH4F in ethylene glycol)were used to anodize the Ti films. The anodized films were subsequently annealed at 600 °C for 4 hrs in an oxygen rich environment to obtain TiO2. The current-voltage(I-V) characteristics of the Pt/TiO2/SiC devices were measured in different concentrations of propene. Exposure to the analyte gas caused a change in the Schottky barrier height and hence a lateral shift in the I-V characteristics. The effective change in the barrier height for 1% propene was calculated as 32.8 meV at 620°C. The dynamic response of the sensors was also investigated and a voltage shift of 157 mV was measured at 620°C during exposure to 1% propene.

Towards proximity-based passenger sensing on public transport buses

While substantial research on intelligent transportation systems has focused on the development of novel wireless communication technologies and protocols, relatively little work has sought to fully exploit proximity-based wireless technologies that passengers actually carry with them today. This paper presents the real-world deployment of a system that exploits public transit bus passengers’ Bluetooth-capable devices to capture and reconstruct micro- and macro-passenger behavior. We present supporting evidence that approximately 12% of passengers already carry Bluetooth-enabled devices and that the data collected on these passengers captures with almost 80 % accuracy the daily fluctuation of actual passengers flows. The paper makes three contributions in terms of understanding passenger behavior: We verify that the length of passenger trips is exponentially bounded, the frequency of passenger trips follows a power law distribution, and the microstructure of the network of passenger movements is polycentric.

Gamifying everyday activities using mobile sensing

The addition of game design elements to non-game contexts has become known as gamification. Previous research has suggested that framing tedious and non-motivating tasks as game-like can make them enjoyable and motivating (e.g., de Oliveira, et al., 2010; Fujiki, et al., 2007; Chiu, et al., 2009). Smartphone applications lend themselves to being gamified as the underlying mobile technology has the ability to sense user activities and their surrounding environment. These sensed activities can be used to implement and enforce game-like rules based around many physical activities (e.g., exercise, travel, or eating). If researchers wish to investigate this area, they first need an existing gamified application to study. However if an appropriate application does not exist then the researcher may need to create their own gamified prototype to study. Unfortunately, there is little previous research that details or explains the design and integration of game elements to non-game mobile applications. This chapter explores this gap and shares a framework that was used to add videogame-like achievements to an orientation mobile application developed for new university students. The framework proved useful and initial results are discussed from two studies. However, further development of the framework is needed, including further consideration of what makes an effective gamified experience.

Dynamic robot path planning using an enhanced simulated annealing approach

Evolutionary computation is an effective tool for solving optimization problems. However, its significant computational demand has limited its real-time and on-line applications, especially in embedded systems with limited computing resources, e.g., mobile robots. Heuristic methods such as the genetic algorithm (GA) based approaches have been investigated for robot path planning in dynamic environments. However, research on the simulated annealing (SA) algorithm, another popular evolutionary computation algorithm, for dynamic path planning is still limited mainly due to its high computational demand. An enhanced SA approach, which integrates two additional mathematical operators and initial path selection heuristics into the standard SA, is developed in this work for robot path planning in dynamic environments with both static and dynamic obstacles. It improves the computing performance of the standard SA significantly while giving an optimal or near-optimal robot path solution, making its real-time and on-line applications possible. Using the classic and deterministic Dijkstra algorithm as a benchmark, comprehensive case studies are carried out to demonstrate the performance of the enhanced SA and other SA algorithms in various dynamic path planning scenarios.

Creating gold nanoprisms directly on quartz crystal microbalance electrodes for mercury vapor sensing

A novel electrochemical route is used to form highly {111}-oriented and size-controlled Au nanoprisms directly onto the electrodes of quartz crystal microbalances (QCMs) which are subsequently used as mercury vapor sensors. The Au nanoprism loaded QCM sensors exhibited excellent response–concentration linearity with a response enhancement of up to ~ 800% over a non-modified sensor at an operating temperature of 28 °C. The increased surface area and atomic-scale features (step/defect sites) introduced during the growth of nanoprisms are thought to play a significant role in enhancing the sensing properties of the Au nanoprisms toward Hg vapor. The sensors are shown to have excellent Hg sensing capabilities in the concentration range of 0.123–1.27 ppmv (1.02–10.55 mg m − 3), with a detection limit of 2.4 ppbv (0.02 mg m − 3) toward Hg vapor when operating at 28 °C, and 17 ppbv (0.15 mg m − 3) at 89 °C, making them potentially useful for air monitoring applications or for monitoring the efficiency of Hg emission control systems in industries such as mining and waste incineration. The developed sensors exhibited excellent reversible behavior (sensor recovery) within 1 h periods, and crucially were also observed to have high selectivity toward Hg vapor in the presence of ethanol, ammonia and humidity, and excellent long-term stability over a 33 day operating period.

Autonomous movement-driven place recognition calibration for generic multi-sensor robot platforms

In this paper we present a method for autonomously tuning the threshold between learning and recognizing a place in the world, based on both how the rodent brain is thought to process and calibrate multisensory data and the pivoting movement behaviour that rodents perform in doing so. The approach makes no assumptions about the number and type of sensors, the robot platform, or the environment, relying only on the ability of a robot to perform two revolutions on the spot. In addition, it self-assesses the quality of the tuning process in order to identify situations in which tuning may have failed. We demonstrate the autonomous movement-driven threshold tuning on a Pioneer 3DX robot in eight locations spread over an office environment and a building car park, and then evaluate the mapping capability of the system on journeys through these environments. The system is able to pick a place recognition threshold that enables successful environment mapping in six of the eight locations while also autonomously flagging the tuning failure in the remaining two locations. We discuss how the method, in combination with parallel work on autonomous weighting of individual sensors, moves the parameter dependent RatSLAM system significantly closer to sensor, platform and environment agnostic operation.

Laser-to-radar sensing redundancy for resilient perception in adverse environmental conditions

This paper presents an approach to promote the integrity of perception systems for outdoor unmanned ground vehicles (UGV) operating in challenging environmental conditions (presence of dust or smoke). The proposed technique automatically evaluates the consistency of the data provided by two sensing modalities: a 2D laser range finder and a millimetre-wave radar, allowing for perceptual failure mitigation. Experimental results, obtained with a UGV operating in rural environments, and an error analysis validate the approach.

Combining multiple sensor modalities for a localisation robust to smoke

This paper proposes an approach to obtain a localisation that is robust to smoke by exploiting multiple sensing modalities: visual and infrared (IR) cameras. This localisation is based on a state-of-the-art visual SLAM algorithm. First, we show that a reasonably accurate localisation can be obtained in the presence of smoke by using only an IR camera, a sensor that is hardly affected by smoke, contrary to a visual camera (operating in the visible spectrum). Second, we demonstrate that improved results can be obtained by combining the information from the two sensor modalities (visual and IR cameras). Third, we show that by detecting the impact of smoke on the visual images using a data quality metric, we can anticipate and mitigate the degradation in performance of the localisation by discarding the most affected data. The experimental validation presents multiple trajectories estimated by the various methods considered, all thoroughly compared to an accurate dGPS/INS reference.

Error modeling and calibration of exteroceptive sensors for accurate mapping applications

Reliable robotic perception and planning are critical to performing autonomous actions in uncertain, unstructured environments. In field robotic systems, automation is achieved by interpreting exteroceptive sensor information to infer something about the world. This is then mapped to provide a consistent spatial context, so that actions can be planned around the predicted future interaction of the robot and the world. The whole system is as reliable as the weakest link in this chain. In this paper, the term mapping is used broadly to describe the transformation of range-based exteroceptive sensor data (such as LIDAR or stereo vision) to a fixed navigation frame, so that it can be used to form an internal representation of the environment. The coordinate transformation from the sensor frame to the navigation frame is analyzed to produce a spatial error model that captures the dominant geometric and temporal sources of mapping error. This allows the mapping accuracy to be calculated at run time. A generic extrinsic calibration method for exteroceptive range-based sensors is then presented to determine the sensor location and orientation. This allows systematic errors in individual sensors to be minimized, and when multiple sensors are used, it minimizes the systematic contradiction between them to enable reliable multisensor data fusion. The mathematical derivations at the core of this model are not particularly novel or complicated, but the rigorous analysis and application to field robotics seems to be largely absent from the literature to date. The techniques in this paper are simple to implement, and they offer a significant improvement to the accuracy, precision, and integrity of mapped information. Consequently, they should be employed whenever maps are formed from range-based exteroceptive sensor data. © 2009 Wiley Periodicals, Inc.

A probabilistic framework to monitor a multi-mode outdoor robot

This paper presents an approach to autonomously monitor the behavior of a robot endowed with several navigation and locomotion modes, adapted to the terrain to traverse. The mode selection process is done in two steps: the best suited mode is firstly selected on the basis of initial information or a qualitative map built on-line by the robot. Then, the motions of the robot are monitored by various processes that update mode transition probabilities in a Markov system. The paper focuses on this latter selection process: the overall approach is depicted, and preliminary experimental results are presented