Resilient Navigation through Probabilistic Modality Reconfiguration

This paper proposes an approach to achieve resilient navigation for indoor mobile robots. Resilient navigation seeks to mitigate the impact of control, localisation, or map errors on the safety of the platform while enforcing the robot’s ability to achieve its goal. We show that resilience to unpredictable errors can be achieved by combining the benefits of independent and complementary algorithmic approaches to navigation, or modalities, each tuned to a particular type of environment or situation. In this paper, the modalities comprise a path planning method and a reactive motion strategy. While the robot navigates, a Hidden Markov Model continually estimates the most appropriate modality based on two types of information: context (information known a priori) and monitoring (evaluating unpredictable aspects of the current situation). The robot then uses the recommended modality, switching between one and another dynamically. Experimental validation with a SegwayRMP- based platform in an office environment shows that our approach enables failure mitigation while maintaining the safety of the platform. The robot is shown to reach its goal in the presence of: 1) unpredicted control errors, 2) unexpected map errors and 3) a large injected localisation fault.

Selection and monitoring of navigation modes for an autonomous rover

Considering the wide spectrum of situations that it may encounter, a robot navigating autonomously in outdoor environments needs to be endowed with several operating modes, for robustness and efficiency reasons. Indeed, the terrain it has to traverse may be composed of flat or rough areas, low cohesive soils such as sand dunes, concrete road etc... Traversing these various kinds of environment calls for different navigation and/or locomotion functionalities, especially if the robot is endowed with different locomotion abilities, such as the robots WorkPartner, Hylos [4], Nomad or the Marsokhod rovers.

Selection and monitoring of navigation modes for an autonomous rover

Considering the wide spectrum of situations that it may encounter, a robot navigating autonomously in outdoor environments needs to be endowed with several operating modes, for robustness and efficiency reasons. Indeed, the terrain it has to traverse may be composed of flat or rough areas, low cohesive soils such as sand dunes, concrete road etc. . .Traversing these various kinds of environment calls for different navigation and/or locomotion functionalities, especially if the robot is endowed with different locomotion abilities, such as the robots WorkPartner, Hylos [4], Nomad or the Marsokhod rovers. Numerous rover navigation techniques have been proposed, each of them being suited to a particular environment context (e.g. path following, obstacle avoidance in more or less cluttered environments, rough terrain traverses...). However, seldom contributions in the literature tackle the problem of selecting autonomously the most suited mode [3]. Most of the existing work is indeed devoted to the passive analysis of a single navigation mode, as in [2]. Fault detection is of course essential: one can imagine that a proper monitoring of the Mars Exploration Rover Opportunity could have avoided the rover to be stuck during several weeks in a dune, by detecting non-nominal behavior of some parameters. But the ability to recover the anticipated problem by switching to a better suited navigation mode would bring higher autonomy abilities, and therefore a better overall efficiency. We propose here a probabilistic framework to achieve this, which fuses environment related and robot related information in order to actively control the rover operations.

Air navigation services in Australia and the United States : a comparative case study

The central document governing the global organization of Air Navigation Services (ANS) is the Convention on International Civil Aviation, commonly referred to as the “Chicago Convention,” whose original version was signed in that city in 1944. In the Convention, Contracting States agreed to ensure the minimum standards of ANS established by ICAO, a specialized United Nations agency created by the Convention. Emanating from obligations under the Chicago Convention, ANS has traditionally provided by departments of national governments. However, there is a widespread trend toward transferring delivery of ANS services outside of line departments of national governments to independent agencies or corporations. The Civil Air Navigation Services Organisation (CANSO), which is the trade association for independent ANS providers, currently counts approximately 60 members, and is steadily growing. However, whatever delivery mechanisms are chosen, national governments remain ultimately responsible for ensuring that adequate ANS services are available. The provision by governments of ANS reflects the responsibility of the state for safety, international relations, and indirectly, the macroeconomic benefits of ensuring a sound infrastructure for aviation. ANS is a “public good” and an “essential good” provided to all aircraft using a country’s airfields and airspace. However, ANS also represents a service that directly benefits only a limited number of users, notably aircraft owners and operators. The idea that the users of the system, rather than the taxpaying public, should incur the costs associated with ANS provision is inherent in the commercialization process. However, ICAO sets out broad principles for the establishment of user charges, which member states are expected to comply with. ICAO states that only distance flown and aircraft weights are acceptable parameters for use in a charging system. These two factors are considered to be easy to measure, bear a reasonable relationship to the value of service received, and do not discriminate due to factors such as where the flight originated or the nation of aircraft registration.

Using performance-based evaluation to close the loop between biological and robotic navigation

In this paper we describe the benefits of a performance-based approach to modeling biological systems for use in robotics. Specifically, we describe the RatSLAM system, a computational model of the navigation processes thought to drive navigation in a part of the rodent brain called the hippocampus. Unlike typical computational modeling approaches, which focus on biological fidelity, RatSLAM’s development cycle has been driven primarily by performance evaluation on robots navigating in a wide variety of challenging, real world environments. We briefly describe three seminal results, two in robotics and one in biology. In addition, we present current research on brain-inspired learning algorithms with the aim of enabling a robot to autonomously learn how best to use its sensor suite to navigate, without requiring any specific knowledge of the robot, sensor types or environment characteristics. Our aim is to drive discussion on the merits of practical, performance-focused implementations of biological models in robotics.

Design of an integrated platform for V2X wireless communications and positioning supporting C-ITS safety applications

In this paper, an integrated inter-vehicles wireless communications and positioning system supporting alternate positioning techniques is proposed to meet the requirements of safety applications of Cooperative Intelligent Transportation Systems (C-ITS). Recent advances have repeatedly demonstrated that road safety problems can be to a large extent addressed via a range of technologies including wireless communications and positioning in vehicular environments. The novel communication stack utilizing a dedicated frequency spectrum (e.g. at 5.9 GHz band), known as Dedicated Short-Range Communications (DSRC), has been particularly designed for Wireless Access in Vehicular Environments (WAVE) to support safety applications in highly dynamic environments. Global Navigation Satellite Systems (GNSS) is another essential enabler to support safety on rail and roads. Although current vehicle navigation systems such as single frequency Global Positioning System (GPS) receivers can provide route guidance with 5-10 meters (road-level) position accuracy, positioning systems utilized in C-ITS must provide position solutions with lane-level and even in-lane-level accuracies based on the requirements of safety applications. This article reviews the issues and technical approaches that are involved in designing a vehicular safety communications and positioning architecture; it also provides technological solutions to further improve vehicular safety by integrating the DSRC and GNSS-based positioning technologies.

Aircraft dynamic navigation for unmanned aerial vehicles

This thesis describes the investigation of an Aircraft Dynamic Navigation (ADN) approach, which incorporates an Aircraft Dynamic Model (ADM) directly into the navigation filter of a fixed-wing aircraft or UAV. The result is a novel approach that offers both performance improvements and increased reliability during short-term GPS outages. This is important in allowing future UAVs to achieve routine, unconstrained, and safe operations in commercial environments. The primary contribution of this research is the formulation Unscented Kalman Filter (UKF) which incorporates a complex, non-linear, laterally and longitudinally coupled, ADM, and sensor suite consisting of a Global Positioning System (GPS) receiver, Inertial Measurement Unit (IMU), Electronic Compass (EC), and Air Data (AD) Pitot Static System.

Examining intuitive navigation in airports

Airports accommodate passengers with a range of prior experience, from frequent flyers, to passengers who fly every couple of years, to those who have never flown before. Passengers with varying levels of prior experience may use different visual elements when navigating the airport. Ensuring all passengers can navigate to the processing activities intuitively is important for passengers, airports and airlines. This paper examines how participants with Low, Medium and High airport familiarity navigate through the departures area at an Australian international airport. Three navigation activities are investigated: (i) navigating to the check-in row, (ii) navigating through the Liquids, Aerosols and Gels (LAGs) preparation area before security screening, and; (iii) navigating to either the boarding gate first or to a discretionary activity first, after exiting customs. In the three activities, differences were observed between the familiarity groups. These differences include the use of different information to locate the check-in desk, different actions when navigating through the LAG preparation area, and evidence that Low familiarity passengers have a desire to locate the boarding gate as soon as possible once through customs. This research provides evidence based design reccomendations for airports to benefit from intuitive passenger navigation.

High-frequency global navigation satellite system’s receivers for airborne gravimetry

The development of global navigation satellite systems (GNSS) provides a solution of many applied problems with increasingly higher quality and accuracy nowadays. Researches that are carried out by the Bavarian Academy of Sciences and Humanities in Munich (BAW) in the field of airborne gravimetry are based on sophisticated data processing from high frequency GNSS receiver for kinematic aircraft positioning. Applied algorithms for inertial acceleration determination are based on the high sampling rate (50Hz) and on reducing of such factors as ionosphere scintillation and multipath at aircraft /antenna near field effects. The quality of the GNSS derived kinematic height are studied also by intercomparison with lift height variations collected by a precise high sampling rate vertical scale [1]. This work is aimed at the ways of more accurate determination of mini-aircraft altitude by means of high frequency GNSS receivers, in particular by considering their dynamic behaviour.

Differential effects of aging on spatial learning through exploratory navigation and map reading

It has been shown that abilities in spatial learning and memory are adversely affected by aging. The present study was conducted to investigate whether increasing age has equal consequences for all types of spatial learning or impacts certain types of spatial learning selectively. Specifically, two major types of spatial learning, exploratory navigation and map reading, were contrasted. By combining a neuroimaging finding that the medial temporal lobe (MTL) is especially important for exploratory navigation and a neurological finding that the MTL is susceptible to age-related atrophy, it was hypothesized that spatial learning through exploratory navigation would exhibit a greater decline in later life than spatial learning through map reading. In an experiment, young and senior participants learned locations of landmarks in virtual environments either by navigating in them in the first-person perspective or by seeing aerial views of the environments. Results showed that senior participants acquired less accurate memories of the layouts of landmarks than young participants when they navigated in the environments, but the two groups did not differ in spatial learning performance when they viewed the environments from the aerial perspective. These results suggest that spatial learning through exploratory navigation is particularly vulnerable to adverse effects of aging, whereas elderly adults may be able to maintain their map reading skills relatively well.

A hierarchical model of goal directed navigation selects trajectories in a visual environment

We have developed a Hierarchical Look-Ahead Trajectory Model (HiLAM) that incorporates the firing pattern of medial entorhinal grid cells in a planning circuit that includes interactions with hippocampus and prefrontal cortex. We show the model’s flexibility in representing large real world environments using odometry information obtained from challenging video sequences. We acquire the visual data from a camera mounted on a small tele-operated vehicle. The camera has a panoramic field of view with its focal point approximately 5 cm above the ground level, similar to what would be expected from a rat’s point of view. Using established algorithms for calculating perceptual speed from the apparent rate of visual change over time, we generate raw dead reckoning information which loses spatial fidelity over time due to error accumulation. We rectify the loss of fidelity by exploiting the loop-closure detection ability of a biologically inspired, robot navigation model termed RatSLAM. The rectified motion information serves as a velocity input to the HiLAM to encode the environment in the form of grid cell and place cell maps. Finally, we show goal directed path planning results of HiLAM in two different environments, an indoor square maze used in rodent experiments and an outdoor arena more than two orders of magnitude larger than the indoor maze. Together these results bridge for the first time the gap between higher fidelity bio-inspired navigation models (HiLAM) and more abstracted but highly functional bio-inspired robotic mapping systems (RatSLAM), and move from simulated environments into real-world studies in rodent-sized arenas and beyond.

An adaptive spherical view representation for navigation in changing environments

Real-world environments such as houses and offices change over time, meaning that a mobile robot’s map will become out of date. In previous work we introduced a method to update the reference views in a topological map so that a mobile robot could continue to localize itself in a changing environment using omni-directional vision. In this work we extend this longterm updating mechanism to incorporate a spherical metric representation of the observed visual features for each node in the topological map. Using multi-view geometry we are then able to estimate the heading of the robot, in order to enable navigation between the nodes of the map, and to simultaneously adapt the spherical view representation in response to environmental changes. The results demonstrate the persistent performance of the proposed system in a long-term experiment.

Long-term experiments with an adaptive spherical view representation for navigation in changing environments

Real-world environments such as houses and offices change over time, meaning that a mobile robot’s map will become out of date. In this work, we introduce a method to update the reference views in a hybrid metrictopological map so that a mobile robot can continue to localize itself in a changing environment. The updating mechanism, based on the multi-store model of human memory, incorporates a spherical metric representation of the observed visual features for each node in the map, which enables the robot to estimate its heading and navigate using multi-view geometry, as well as representing the local 3D geometry of the environment. A series of experiments demonstrate the persistence performance of the proposed system in real changing environments, including analysis of the long-term stability.

‘Structuring’ judicial sentencing discretion : consistency, guidance or pandering to the punitive?

Until quite recently, most Australian jurisdictions gave statutory force to the principle of imprisonment as a sanction of last resort, reflecting its status as the most punitive sentencing option open to the court.1 That principle gave primary discretion as to whether incarceration was the most appropriate means of achieving the purpose of a sentence to the sentencing court, which received all of the information relevant to the offence, the offender and any victim(s). The disestablishment of this principle is symptomatic of an increasing erosion of judicial discretion with respect to sentencing, which appears to be resulting in some extremely punitive consequences.