This paper describes the architecture and implementation of an autonomous passenger vehicle designed to navigate using locally perceived information in preference to potentially inaccurate or incomplete map data. The vehicle architecture was designed to handle the original DARPA Urban Challenge requirements of perceiving and navigating a road network with segments defined by sparse waypoints. The vehicle implementation includes many heterogeneous sensors with significant communications and computation bandwidth to capture and process high-resolution, high-rate sensor data. The output of the comprehensive environmental sensing subsystem is fed into a kinodynamic motion planning algorithm to generate all vehicle motion. The requirements of driving in lanes, three-point turns, parking, and maneuvering through obstacle fields are all generated with a unified planner. A key aspect of the planner is its use of closed-loop simulation in a rapidly exploring randomized trees algorithm, which can randomly explore the space while efficiently generating smooth trajectories in a dynamic and uncertain environment. The overall system was realized through the creation of a powerful new suite of software tools for message passing, logging, and visualization. These innovations provide a strong platform for future research in autonomous driving in global positioning system-denied and highly dynamic environments with poor a priori information. C 2008 Wiley Periodicals, Inc.

This paper describes the architecture and implementation of an autonomous passenger vehicle designed to navigate using locally perceived information in preference to potentially inaccurate or incomplete map data. The vehicle architecture was designed to handle the original DARPA Urban Challenge requirements of perceiving and navigating a road network with segments defined by sparse waypoints. The vehicle implementation includes many heterogeneous sensors with significant communications and computation bandwidth to capture and process high-resolution, high-rate sensor data. The output of the comprehensive environmental sensing subsystem is fed into a kino-dynamic motion planning algorithm to generate all vehicle motion. The requirements of driving in lanes, three-point turns, parking, and maneuvering through obstacle fields are all generated with a unified planner. A key aspect of the planner is its use of closed-loop simulation in a Rapidly-exploring Randomized Trees (RRT) algorithm, which can randomly explore the space while efficiently generating smooth trajectories in a dynamic and uncertain environment. The overall system was realized through the creation of a powerful new suite of software tools for message-passing, logging, and visualization. These innovations provide a strong platform for future research in autonomous driving in GPS-denied and highly dynamic environments with poor a priori information.

This study shows that AFCs and WFCs cannot be assumed to register equal values of pressure. It has further shown that even when the p readings are compared with their value at the start of a test, a divergence of values of up to 10 cmH O remains. If AFCs are used, care must be taken to compensate for any p variations that occur during patient movement. Before AFCs are adopted, new normal values for resting pressures need to be developed to allow good quality AFC pressure readings to be made. Neurourol. Urodynam. 35:926-933, 2016. © 2015 Wiley Periodicals, Inc.

Detrusor underactivity (DUA) is defined as a voiding contraction of reduced strength and/or duration, which prolongs urination and/or prevents complete emptying of the bladder within a 'normal' period of time. This issue is associated with voiding and postmicturition urinary symptoms, and can predispose to urinary infections and acute urinary retention. The aetiology of DUA is influenced by multiple factors, including ageing, bladder outlet obstruction, neurological disease, and autonomic denervation. The true prevalence of this condition remains unknown, as most data come from referral populations. Urodynamic testing is used to diagnose the condition, either by assessing the relationship between bladder pressures and urinary flow, or by interrupting voiding to measure detrusor pressure change under isovolumetric conditions. Current treatments for DUA have poor efficacy and tolerability, and often fail to improve quality of life; muscarinic receptor agonists, in particular, have limited efficacy and frequent adverse effects. Bladder emptying might be achieved through Valsalva straining, and intermittent or indwelling catheterization, although sacral nerve stimulation can reduce dependency on catheterization. Novel stem-cell-based therapies have been attempted; however, new drugs that increase contractility are currently largely conceptual, and the complex pathophysiology of DUA, difficulty achieving organ specificity of treatment, the limited availability of animal models, and the subjective nature of current outcome measures must be addressed to facilitate the development of such agents.