An Incremental Navigation Localization Methodology for Application to Semi-Autonomous Mobile Robotic Platforms to Assist Individuals Having Severe Motor Disabilities.

In the present work, the author explores the issues surrounding the design and development of an intelligent wheelchair platform incorporating the semi-autonomous system paradigm, to meet the needs of individuals with severe motor disabilities. The author presents a discussion of the problems of navigation that must be solved before any system of this type can be instantiated, and enumerates the general design issues that must be addressed by the designers of systems of this type. This discussion includes reviews of various methodologies that have been proposed as solutions to the problems considered. Next, the author introduces a new navigation method, called Incremental Signature Recognition (ISR), for use by semi-autonomous systems in structured environments. This method is based on the recognition, recording, and tracking of environmental discontinuities: sensor reported anomalies in measured environmental parameters. The author then proposes a robust, redundant, dynamic, self-diagnosing sensing methodology for detecting and compensating for hidden failures of single sensors and sensor idiosyncrasies. This technique is optimized for the detection of spatial discontinuity anomalies. Finally, the author gives details of an effort to realize a prototype ISR based system, along with insights into the various implementation choices made

Intuitive Robot Teleoperation Based on Haptic Feedback and 3D Visualization

Robots are required in many jobs. The jobs related to tele-operation may be very challenging and often require reaching a destination quickly and with minimum collisions. In order to succeed in these jobs, human operators are asked to tele-operate a robot manually through a user interface. The design of a user interface and of the information provided in it, become therefore critical elements for the successful completion of robot tele-operation tasks. Effective and timely robot tele-navigation mainly relies on the intuitiveness provided by the interface and on the richness and presentation of the feedback given. This project investigated the use of both haptic and visual feedbacks in a user interface for robot tele-navigation. The aim was to overcome some of the limitations observed in a state of the art works, turning what is sometimes described as contrasting into an added value to improve tele-navigation performance. The key issue is to combine different human sensory modalities in a coherent way and to benefit from 3-D vision too. The proposed new approach was inspired by how visually impaired people use walking sticks to navigate. Haptic feedback may provide helpful input to a user to comprehend distances to surrounding obstacles and information about the obstacle distribution. This was proposed to be achieved entirely relying on on-board range sensors, and by processing this input through a simple scheme that regulates magnitude and direction of the environmental force-feedback provided to the haptic device. A specific algorithm was also used to render the distribution of very close objects to provide appropriate touch sensations. Scene visualization was provided by the system and it was shown to a user coherently to haptic sensation. Different visualization configurations, from multi-viewpoint observation to 3-D visualization, were proposed and rigorously assessed through experimentations, to understand the advantages of the proposed approach and performance variations among different 3-D display technologies. Over twenty users were invited to participate in a usability study composed by two major experiments. The first experiment focused on a comparison between the proposed haptic-feedback strategy and a typical state of the art approach. It included testing with a multi-viewpoint visual observation. The second experiment investigated the performance of the proposed haptic-feedback strategy when combined with three different stereoscopic-3D visualization technologies. The results from the experiments were encouraging and showed good performance with the proposed approach and an improvement over literature approaches to haptic feedback in robot tele-operation. It was also demonstrated that 3-D visualization can be beneficial for robot tele-navigation and it will not contrast with haptic feedback if it is properly aligned to it. Performance may vary with different 3-D visualization technologies, which is also discussed in the presented work

Detecting on-street parking spaces in smart cities: Performance evaluation of fixed and mobile sensing systems

As the number of vehicles continues to grow, parking spaces are at a premium in city streets. In addition, due to the lack of knowledge about street parking spaces, heuristic circling in the streets not only costs drivers’ time and fuel, but also increases city congestion. In the wake of the recent trend to build convenient, green and energy-efficient smart cities, common techniques adopted by high-profile smart parking systems are reviewed, and the performance of the various approaches are compared. A mobile sensing unit has been developed as an alternative to the fixed sensing approach. It is mounted on the passenger side of a car to measure the distance from the vehicle to the nearest roadside obstacle. By extracting parked vehicles’ features from the collected trace, a supervised learning algorithm has been developed to estimate roadside parking occupancy. Multiple road tests were conducted around Wheatley (Oxfordshire) and Guildford (Surrey) in the UK. In the case of accurate GPS readings, enhanced by a map matching technique, the accuracy of the system is above 90%. A quantity estimation model is derived to calculate the density of sensing units required to cover urban streets. The estimation is quantitatively compared to a fixed sensing solution. The results show that the mobile sensing approach can perform at the same level as fixed sensing solutions when accurate location information is available but substantially fewer sensors are needed compared to the fixed sensing system

A non-holonomic, highly human-in-the-loop compatible, assistive mobile robotic platform guidance navigation and control strategy

The provision of assistive mobile robotics for empowering and providing independence to the infirm, disabled and elderly in society has been the subject of much research. The issue of providing navigation and control assistance to users, enabling them to drive their powered wheelchairs effectively, can be complex and wide-ranging; some users fatigue quickly and can find that they are unable to operate the controls safely, others may have brain injury re-sulting in periodic hand tremors, quadriplegics may use a straw-like switch in their mouth to provide a digital control signal. Advances in autonomous robotics have led to the development of smart wheelchair systems which have attempted to address these issues; however the autonomous approach has, ac-cording to research, not been successful; users reporting that they want to be active drivers and not passengers. Recent methodologies have been to use collaborative or shared control which aims to predict or anticipate the need for the system to take over control when some pre-decided threshold has been met, yet these approaches still take away control from the us-er. This removal of human supervision and control by an autonomous system makes the re-sponsibility for accidents seriously problematic. This thesis introduces a new human-in-the-loop control structure with real-time assistive lev-els. One of these levels offers improved dynamic modelling and three of these levels offer unique and novel real-time solutions for: collision avoidance, localisation and waypoint iden-tification, and assistive trajectory generation. This architecture and these assistive functions always allow the user to remain fully in control of any motion of the powered wheelchair, shown in a series of experiments

Effects of automation on situation awareness in controlling robot teams

Declines in situation awareness (SA) often accompany automation. Some of these effects have been characterized as out-of-the-loop, complacency, and automation bias. Increasing autonomy in multi-robot control might be expected to produce similar declines in operators’ SA. In this paper we review a series of experiments in which automation is introduced in controlling robot teams. Automating path planning at a foraging task improved both target detection and localization which is closely tied to SA. Timing data, however, suggested small declines in SA for robot location and pose. Automation of image acquisition, by contrast, led to poorer localization. Findings are discussed and alternative explanations involving shifts in strategy proposed