Prosecutorial guidelines for voluntary euthanasia and assisted suicide : autonomy, public confidence and high quality decision-making

This article proposes offence-specific guidelines for how prosecutorial discretion should be exercised in cases of voluntary euthanasia and assisted suicide. Similar guidelines have been produced in England and Wales but we consider them to be deficient in a number of respects, including that they lack a set of coherent guiding principles. In light of these concerns, we outline an approach to constructing alternative guidelines that begins with identifying three guiding principles that we argue are appropriate for this purpose: respect for autonomy, the need for high quality prosecutorial decision-making and the importance of public confidence in that decision-making.

Skype : a communications framework for robotics

This paper describes an architecture for robotic telepresence and teleoperation based on the well known tools ROS and Skype. We discuss how Skype can be used as a framework for robotic communication and can be integrated into a ROS/Linux framework to allow a remote user to not only interact with people near the robot, but to view maps, sensory data, robot pose and to issue commands to the robot’s navigation stack. This allows the remote user to exploit the robot’s autonomy, providing a much more convenient navigation interface than simple remote joysticking.

Management of heterogeneous UAVs through a capability framework of UAV’s functional autonomy

An increased interest in utilising groups of Unmanned Aerial Vehicles (UAVs) with heterogeneous capabilities and autonomy is presenting the challenge to effectively manage such during missions and operations. This has been the focus of research in recent years, moving from a traditional UAV management paradigm of n-to-1 (n operators for one UAV, with n being at least two operators) toward 1-to-n (one operator, multiple UAVs). This paper has expanded on the authors’ previous work on UAV functional capability framework, by incorporating the concept of Functional Level of Autonomy (F-LOA) with two configurations: The lower F-LOA configuration contains sufficient information for the operator to generate solutions and make decisions to address perturbation events. Alternatively, the higher F-LOA configuration presents information reflecting on the F-LOA of the UAV, allowing the operator to interpret solutions and decisions generated autonomously, and decide whether to veto from this decision.

Feminist ethics and menopause : autonomy and decision-making in primary medical care

The construction of menopause as a long-term risk to health and the adoption of discourses of prevention has made necessary a decision by women about medical treatment; specifically regarding the use of hormone replacement therapy. In a study of general practitioners’ accounts of menopause and treatment in Australia, women's ‘choice’, ‘informed decision-making’ and ‘empowerment’ were key themes through which primary medical care for women at menopause was presented. These accounts create a position for women defined by the concept of individual choice and an ethic of autonomy. These data are a basis for theorising more generally in this paper. We critically examine the construct of ‘informed decision-making’ in relation to several approaches to ethics including bioethics and a range of feminist ethics. We identify the intensification of power relations produced by an ethic of autonomy and discuss the ways these considerations inform a feminist ethics of decision-making by women. We argue that an ‘ethic of autonomy’ and an ‘offer of choice’ in relation to health care for women at menopause, far from being emancipatory, serves to intensify power relations. The dichotomy of choice, to take or not to take hormone replacement therapy, is required to be a choice and is embedded in relations of power and bioethical discourse that construct meanings about what constitutes decision-making at menopause. The deployment of the principle of autonomy in medical practice limits decision-making by women precisely because it is detached from the construction of meaning and the self and makes invisible the relations of power of which it is a part.

Online calibration of stereo rigs for long-term autonomy

Stereo-based visual odometry algorithms are heavily dependent on an accurate calibration of the rigidly fixed stereo pair. Even small shifts in the rigid transform between the cameras can impact on feature matching and 3D scene triangulation, adversely affecting pose estimates and applications dependent on long-term autonomy. In many field-based scenarios where vibration, knocks and pressure change affect a robotic vehicle, maintaining an accurate stereo calibration cannot be guaranteed over long periods. This paper presents a novel method of recalibrating overlapping stereo camera rigs from online visual data while simultaneously providing an up-to-date and up-to-scale pose estimate. The proposed technique implements a novel form of partitioned bundle adjustment that explicitly includes the homogeneous transform between a stereo camera pair to generate an optimal calibration. Pose estimates are computed in parallel to the calibration, providing online recalibration which seamlessly integrates into a stereo visual odometry framework. We present results demonstrating accurate performance of the algorithm on both simulated scenarios and real data gathered from a wide-baseline stereo pair on a ground vehicle traversing urban roads.

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.

One robot, eight hours, and twenty four thousand people

This paper presents an account of an autonomous mobile robot deployment in a densely crowded public event with thousands of people from different age groups attending. The robot operated for eight hours on an open floor surrounded by tables, chairs and massive touchscreen displays. Due to the large number of people who were in close vicinity of the robot, different safety measures were implemented including the use of no-go zones which prevent the robot from blocking emergency exits or moving too close to the display screens. The paper presents the lessons learnt and experiences obtained from this experiment, and provides a discussion about the state of mobile service robots in such crowded environments.

Continuous appearance-based localisation and mapping

This thesis presents a novel approach to mobile robot navigation using visual information towards the goal of long-term autonomy. A novel concept of a continuous appearance-based trajectory is proposed in order to solve the limitations of previous robot navigation systems, and two new algorithms for mobile robots, CAT-SLAM and CAT-Graph, are presented and evaluated. These algorithms yield performance exceeding state-of-the-art methods on public benchmark datasets and large-scale real-world environments, and will help enable widespread use of mobile robots in everyday applications.

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.

RatSLAM : using models of rodent hippocampus for robot navigation and beyond

We describe recent biologically-inspired mapping research incorporating brain-based multi-sensor fusion and calibration processes and a new multi-scale, homogeneous mapping framework. We also review the interdisciplinary approach to the development of the RatSLAM robot mapping and navigation system over the past decade and discuss the insights gained from combining pragmatic modelling of biological processes with attempts to close the loop back to biology. Our aim is to encourage the pursuit of truly interdisciplinary approaches to robotics research by providing successful case studies.

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.

Selection et controle de modes de deplacement pour un robot mobile autonome en environnements naturels

Autonomous navigation and locomotion of a mobile robot in natural environments remain a rather open issue. Several functionalities are required to complete the usual perception/decision/action cycle. They can be divided in two main categories : navigation (perception and decision about the movement) and locomotion (movement execution). In order to be able to face the large range of possible situations in natural environments, it is essential to make use of various kinds of complementary functionalities, defining various navigation and locomotion modes. Indeed, a number of navigation and locomotion approaches have been proposed in the literature for the last years, but none can pretend being able to achieve autonomous navigation and locomotion in every situation. Thus, it seems relevant to endow an outdoor mobile robot with several complementary navigation and locomotion modes. Accordingly, the robot must also have means to select the most appropriate mode to apply. This thesis proposes the development of such a navigation/locomotion mode selection system, based on two types of data: an observation of the context to determine in what kind of situation the robot has to achieve its movement and an evaluation of the behavior of the current mode, made by monitors which influence the transitions towards other modes when the behavior of the current one is considered as non satisfying. Hence, this document introduces a probabilistic framework for the estimation of the mode to be applied, some navigation and locomotion modes used, a qualitative terrain representation method (based on the evaluation of a difficulty computed from the placement of the robot's structure on a digital elevation map), and monitors that check the behavior of the modes used (evaluation of rolling locomotion efficiency, robot's attitude and configuration watching. . .). Some experimental results obtained with those elements integrated on board two different outdoor robots are presented and discussed.

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