Looming aircraft threats : shape-based passive ranging of aircraft from monocular vision

This paper proposes new techniques for aircraft shape estimation, passive ranging, and shape-adaptive hidden Markov model filtering which are suitable for a monocular vision-based non-cooperative collision avoidance system. Vision-based passive ranging is an important missing technology that could play a significant role in resolving the sense-and-avoid problem in un-manned aerial vehicles (UAVs); a barrier hindering the wider adoption of UAVs for civilian applications. The feasibility of the pro- posed shape estimation, passive ranging and shape-adaptive filtering techniques is evaluated on flight test data.

Leader vision and diffusion of HR policy during change

Purpose – This paper utilizes diffusion of innovation theory in order to investigate and understand the relationships between HR policies on employee change-related outcomes. In addition, the aim is to explore the role of leader vision at different hierarchical levels in the organization in terms of the relationship of HR policy with employee change-related outcomes. Design/methodology/approach – This quantitative study was conducted in one large Australian government department undergoing major restructuring and cultural change. Data from 624 employees were analyzed in relation to knowledge of HR policies (awareness and clarity), leader vision (organizational and divisional), and change-related outcomes. Findings –Policy knowledge (awareness and clarity) does not have a direct impact on employee change-related outcomes. It is the implementation of policies through the divisional leader that begins to enable favorable employee outcomes. Research limitations/implications – Future research should employ a longitudinal design to investigate relationships over time, and also examine the importance of communication medium and individual preferences in relation to leader vision. Originality/value - This research extends the application of diffusion of innovation theory and leader vision theory to investigate the relationship between HR policy, leader vision, and employees’ change-related outcomes.

Inspection of pole-like structures using a vision-controlled VTOL UAV and shared autonomy

We present an approach for the inspection of vertical pole-like infrastructure using a vertical take-off and landing (VTOL) unmanned aerial vehicle and shared autonomy. Inspecting vertical structures, such as light and power distribution poles, is a time consuming, dangerous and expensive task with high operator workload. To address these issues, we propose a VTOL platform that can operate at close-quarters, whilst maintaining a safe stand-off distance and rejecting environmental disturbances. We adopt an Image based Visual Servoing (IBVS) technique using only two line features to stabilise the vehicle with respect to a pole. Visual, inertial and sonar data are used, making the approach suitable for indoor or GPS-denied environments. Results from simulation and outdoor flight experiments demonstrate the system is able to successfully inspect and circumnavigate a pole.

Short-data recursive HMM parameter estimation for rapid vision-based aircraft heading estimation

Rapid recursive estimation of hidden Markov Model (HMM) parameters is important in applications that place an emphasis on the early availability of reasonable estimates (e.g. for change detection) rather than the provision of longer-term asymptotic properties (such as convergence, convergence rate, and consistency). In the context of vision- based aircraft (image-plane) heading estimation, this paper suggests and evaluates the short-data estimation properties of 3 recursive HMM parameter estimation techniques (a recursive maximum likelihood estimator, an online EM HMM estimator, and a relative entropy based estimator). On both simulated and real data, our studies illustrate the feasibility of rapid recursive heading estimation, but also demonstrate the need for careful step-size design of HMM recursive estimation techniques when these techniques are intended for use in applications where short-data behaviour is paramount.

Configuring retroreflective markings to enhance the night-time conspicuity of road workers

This study investigated whether the night-time conspicuity of road workers can be enhanced by positioning retroreflective strips on the moveable joints in patterns that convey varying degrees of biological motion. Participants were 24 visually normal adults (12 young M = 26.8 years; 12 older M = 72.9 years). Visual acuity, contrast sensitivity and glare sensitivity were recorded for each participant. Experimenters acting as road workers walked in place on a closed road circuit within simulated road work sites, facing either the oncoming driver or the roadway (presenting sideways to the driver) and wearing one of four clothing conditions: (i) standard road worker vest; (ii) standard vest plus thigh-mounted retroreflective strips; (iii) standard vest plus retroreflective strips on ankles and knees; (iv) standard vest plus retroreflective strips positioned on the extremities in a configuration that conveyed biological motion (“biomotion”). As they drove along the closed road participants were instructed to press a button to indicate when they first recognized that a road worker was present. The results demonstrated that regardless of the direction of walking, road workers wearing biomotion clothing were recognized at significantly (p < 0.05) longer distances (3×), relative to the standard vest alone. Response distances were significantly shorter for the older drivers. Contrast sensitivity was a better predictor of the ability to recognize road workers than was visual acuity or glare sensitivity. We conclude that adding retroreflective strips in the biomotion configuration can significantly improve road worker conspicuity regardless of the road worker's orientation and the age of the driver.

Seeing pedestrians at night : effect of driver age and visual abilities

Purpose To quantify the effects of driver age on night-time pedestrian conspicuity, and to determine whether individual differences in visual performance can predict drivers' ability to recognise pedestrians at night. Methods Participants were 32 visually normal drivers (20 younger: M = 24.4 years ± 6.4 years; 12 older: M = 72.0 years ± 5.0 years). Visual performance was measured in a laboratory-based testing session including visual acuity, contrast sensitivity, motion sensitivity and the useful field of view. Night-time pedestrian recognition distances were recorded while participants drove an instrumented vehicle along a closed road course at night; to increase the workload of drivers, auditory and visual distracter tasks were presented for some of the laps. Pedestrians walked in place, sideways to the oncoming vehicles, and wore either a standard high visibility reflective vest or reflective tape positioned on the movable joints (biological motion). Results Driver age and pedestrian clothing significantly (p < 0.05) affected the distance at which the drivers first responded to the pedestrians. Older drivers recognised pedestrians at approximately half the distance of the younger drivers and pedestrians were recognised more often and at longer distances when they wore a biological motion reflective clothing configuration than when they wore a reflective vest. Motion sensitivity was an independent predictor of pedestrian recognition distance, even when controlling for driver age. Conclusions The night-time pedestrian recognition capacity of older drivers was significantly worse than that of younger drivers. The distance at which drivers first recognised pedestrians at night was best predicted by a test of motion sensitivity.

Unsupervised online learning of condition-invariant images for place recognition

This paper presents an online, unsupervised training algorithm enabling vision-based place recognition across a wide range of changing environmental conditions such as those caused by weather, seasons, and day-night cycles. The technique applies principal component analysis to distinguish between aspects of a location’s appearance that are condition-dependent and those that are condition-invariant. Removing the dimensions associated with environmental conditions produces condition-invariant images that can be used by appearance-based place recognition methods. This approach has a unique benefit – it requires training images from only one type of environmental condition, unlike existing data-driven methods that require training images with labelled frame correspondences from two or more environmental conditions. The method is applied to two benchmark variable condition datasets. Performance is equivalent or superior to the current state of the art despite the lesser training requirements, and is demonstrated to generalise to previously unseen locations.

Capturing natural-colour 3D models of insects for species discovery and diagnostics

Collections of biological specimens are fundamental to scientific understanding and characterization of natural diversity - past, present and future. This paper presents a system for liberating useful information from physical collections by bringing specimens into the digital domain so they can be more readily shared, analyzed, annotated and compared. It focuses on insects and is strongly motivated by the desire to accelerate and augment current practices in insect taxonomy which predominantly use text, 2D diagrams and images to describe and characterize species. While these traditional kinds of descriptions are informative and useful, they cannot cover insect specimens "from all angles" and precious specimens are still exchanged between researchers and collections for this reason. Furthermore, insects can be complex in structure and pose many challenges to computer vision systems. We present a new prototype for a practical, cost-effective system of off-the-shelf components to acquire natural-colour 3D models of insects from around 3 mm to 30 mm in length. ("Natural-colour" is used to contrast with "false-colour", i.e., colour generated from, or applied to, gray-scale data post-acquisition.) Colour images are captured from different angles and focal depths using a digital single lens reflex (DSLR) camera rig and two-axis turntable. These 2D images are processed into 3D reconstructions using software based on a visual hull algorithm. The resulting models are compact (around 10 megabytes), afford excellent optical resolution, and can be readily embedded into documents and web pages, as well as viewed on mobile devices. The system is portable, safe, relatively affordable, and complements the sort of volumetric data that can be acquired by computed tomography. This system provides a new way to augment the description and documentation of insect species holotypes, reducing the need to handle or ship specimens. It opens up new opportunities to collect data for research, education, art, entertainment, biodiversity assessment and biosecurity control. © 2014 Nguyen et al.

A novel tuning method for advanced line drop compensator and its application to response coordination of distributed generation with voltage regulating devices

Nowadays, integration of small-scale electricity generators, known as Distributed Generation (DG), into distribution networks has become increasingly popular. This tendency together with the falling price of DG units has a great potential in giving the DG a better chance to participate in voltage regulation process, in parallel with other regulating devices already available in the distribution systems. The voltage control issue turns out to be a very challenging problem for distribution engineers, since existing control coordination schemes need to be reconsidered to take into account the DG operation. In this paper, a control coordination approach is proposed, which is able to utilize the ability of the DG as a voltage regulator, and at the same time minimize the interaction of DG with another DG or other active devices, such as On-load Tap Changing Transformer (OLTC). The proposed technique has been developed based on the concepts of protection principles (magnitude grading and time grading) for response coordination of DG and other regulating devices and uses Advanced Line Drop Compensators (ALDCs) for implementation. A distribution feeder with tap changing transformer and DG units has been extracted from a practical system to test the proposed control technique. The results show that the proposed method provides an effective solution for coordination of DG with another DG or voltage regulating devices and the integration of protection principles has considerably reduced the control interaction to achieve the desired voltage correction.

An efficient forward-backward algorithm to MSDEPP including batteries and voltage control devices

Electric distribution networks are now in the era of transition from passive to active distribution networks with the integration of energy storage devices. Optimal usage of batteries and voltage control devices along with other upgrades in network needs a distribution expansion planning (DEP) considering inter-temporal dependencies of stages. This paper presents an efficient approach for solving multi-stage distribution expansion planning problems (MSDEPP) based on a forward-backward approach considering energy storage devices such as batteries and voltage control devices such as voltage regulators and capacitors. The proposed algorithm is compared with three other techniques including full dynamic, forward fill-in, backward pull-out from the point of view of their precision and their computational efficiency. The simulation results for the IEEE 13 bus network show the proposed pseudo-dynamic forward-backward approach presents good efficiency in precision and time of optimization.