Spatial mapping and map exploitation : a bio-inspired engineering perspective

Probabilistic robot mapping techniques can produce high resolution, accurate maps of large indoor and outdoor environments. However, much less progress has been made towards robots using these maps to perform useful functions such as efficient navigation. This paper describes a pragmatic approach to mapping system development that considers not only the map but also the navigation functionality that the map must provide. We pursue this approach within a bio-inspired mapping context, and use esults from robot experiments in indoor and outdoor environments to demonstrate its validity. The research attempts to stimulate new research directions in the field of robot mapping with a proposal for a new approach that has the potential to lead to more complete mapping and navigation systems.

Cerebellar augmented joint control for a humanoid robot

The joints of a humanoid robot experience disturbances of markedly different magnitudes during the course of a walking gait. Consequently, simple feedback control techniques poorly track desired joint trajectories. This paper explores the addition of a control system inspired by the architecture of the cerebellum to improve system response. This system learns to compensate the changes in load that occur during a cycle of motion. The joint compensation scheme, called Trajectory Error Learning, augments the existing feedback control loop on a humanoid robot. The results from tests on the GuRoo platform show an improvement in system response for the system when augmented with the cerebellar compensator.

Constructing the hallucinations of psychosis in Virtual Reality

Schizophrenia is a mental disorder affecting 1-2% of the population and it is estimated 12-16% of hospital beds in Australia are occupied by patients with psychosis. The suicide rate for patients with this diagnosis is higher than that of the general population. Any technique which enhances training and treatment of this disorder will have a significant societal and economic impact. A significant research project using Virtual Reality (VR), in which both visual and auditory hallucinations are simulated, is currently being undertaken at the University of Queensland. The virtual environments created by the new software are expected to enhance the experiential learning outcomes of medical students by enabling them to experience the inner world of a patient with psychosis. In addition the Virtual Environment has the potential to provide a technologically advanced therapeutic setting where behavioral, exposure therapies can be conducted with exactly controlled exposure stimuli with an expected reduction in risk of harm. This paper reports on the current work of the project, previous stages of software development and future educational and clinical applications of the Virtual Environments. (C) 2004 Elsevier Ltd. All rights reserved.

RatSLAM : a hippocampal model for simultaneous localization and mapping

The work presents a new approach to the problem of simultaneous localization and mapping - SLAM - inspired by computational models of the hippocampus of rodents. The rodent hippocampus has been extensively studied with respect to navigation tasks, and displays many of the properties of a desirable SLAM solution. RatSLAM is an implementation of a hippocampal model that can perform SLAM in real time on a real robot. It uses a competitive attractor network to integrate odometric information with landmark sensing to form a consistent representation of the environment. Experimental results show that RatSLAM can operate with ambiguous landmark information and recover from both minor and major path integration errors.

Probabilistic visual recognition of artificial landmarks for simultaneous localization and mapping

Probabilistic robotics, most often applied to the problem of simultaneous localisation and mapping (SLAM), requires measures of uncertainly to accompany observations of the environment. This paper describes how uncertainly can be characterised for a vision system that locates coloured landmark in a typical laboratory environment. The paper describes a model of the uncertainly in segmentation, the internal camera model and the mounting of the camera on the robot. It =plains the implementation of the system on a laboratory robot, and provides experimental results that show the coherence of the uncertainly model,

Cyclist visibility at night : perceptions of visibility do not necessarily match reality

Visibility limitations make cycling at night particularly dangerous. We previously reported cyclists’ perceptions of their own visibility at night and identified clothing configurations that made them feel visible. In this study we sought to determine whether these self-perceptions reflect actual visibility when wearing these clothing configurations. In a closed-road driving environment, cyclists wore black clothing, a fluorescent vest, a reflective vest, or a reflective vest plus ankle and knee reflectors. Drivers recognised more cyclists wearing the reflective vest plus reflectors (90%) than the reflective vest alone (50%), fluorescent vest (15%) or black clothing (2%). Older drivers recognised the cyclists less often than younger drivers (51% vs 27%). The findings suggest that reflective ankle and knee markings are particularly valuable at night, while fluorescent clothing is not. Cyclists wearing fluorescent clothing may be at particular risk if they incorrectly believe themselves to be conspicuous to drivers at night.

Hybrid robot control and SLAM for persistent navigation and mapping

For a mobile robot to operate autonomously in real-world environments, it must have an effective control system and a navigation system capable of providing robust localization, path planning and path execution. In this paper we describe the work investigating synergies between mapping and control systems. We have integrated development of a control system for navigating mobile robots and a robot SLAM system. The control system is hybrid in nature and tightly coupled with the SLAM system; it uses a combination of high and low level deliberative and reactive control processes to perform obstacle avoidance, exploration, global navigation and recharging, and draws upon the map learning and localization capabilities of the SLAM system. The effectiveness of this hybrid, multi-level approach was evaluated in the context of a delivery robot scenario. Over a period of two weeks the robot performed 1143 delivery tasks to 11 different locations with only one delivery failure (from which it recovered), travelled a total distance of more than 40km, and recharged autonomously a total of 23 times. In this paper we describe the combined control and SLAM system and discuss insights gained from its successful application in a real-world context.

A research opportunity : “3D-ROSE” : virtual reality preparation for children having radiotherapy or imaging procedures

Professor Christian Langton is a medical physicist at Queensland University of Technology in Brisbane. He has developed a way of preparing children who are about to have either radiotherapy or MRI imaging procedures and is seeking research partners to develop and test these further. This is a great opportunity for nurses interested in research, and who have access to a children’s hospital, to work with Professor Langton on some truly innovative, multidisciplinary research.