Automating Vehicles by Deep Reinforcement Learning using Task Separation with Hill Climbing

Within the context of autonomous driving a model-based reinforcement learning algorithm is proposed for the design of neural network-parameterized controllers. Classical model-based control methods, which include sampling- and lattice-based algorithms and model predictive control, suffer from the trade-off between model complexity and computational burden required for the online solution of expensive optimization or search problems at every short sampling time. To circumvent this trade-off, a 2-step procedure is motivated: first learning of a controller during offline training based on an arbitrarily complicated mathematical system model, before online fast feedforward evaluation of the trained controller. The contribution of this paper is the proposition of a simple gradient-free and model-based algorithm for deep reinforcement learning using task separation with hill climbing (TSHC). In particular, (i) simultaneous training on separate deterministic tasks with the purpose of encoding many motion primitives in a neural network, and (ii) the employment of maximally sparse rewards in combination with virtual velocity constraints (VVCs) in setpoint proximity are advocated.Comment: 10 pages, 6 figures, 1 tabl

Sampling-based Motion Planning via Control Barrier Functions

Robot motion planning is central to real-world autonomous applications, such as self-driving cars, persistence surveillance, and robotic arm manipulation. One challenge in motion planning is generating control signals for nonlinear systems that result in obstacle free paths through dynamic environments. In this paper, we propose Control Barrier Function guided Rapidly-exploring Random Trees (CBF-RRT), a sampling-based motion planning algorithm for continuous-time nonlinear systems in dynamic environments. The algorithm focuses on two objectives: efficiently generating feasible controls that steer the system toward a goal region, and handling environments with dynamical obstacles in continuous time. We formulate the control synthesis problem as a Quadratic Program (QP) that enforces Control Barrier Function (CBF) constraints to achieve obstacle avoidance. Additionally, CBF-RRT does not require nearest neighbor or collision checks when sampling, which greatly reduce the run-time overhead when compared to standard RRT variants

Processing of aluminum-graphite particulate metal matrix composites by advanced shear technology

Copyright @ 2009 ASM International. This paper was published in Journal of Materials Engineering and Performance 18(9) and is made available as an electronic reprint with the permission of ASM International. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplications of any material in this paper for a fee or for commercial purposes, or modification of the content of this paper are prohibited.To extend the possibilities of using aluminum/graphite composites as structural materials, a novel process is developed. The conventional methods often produce agglomerated structures exhibiting lower strength and ductility. To overcome the cohesive force of the agglomerates, a melt conditioned high-pressure die casting (MC-HPDC) process innovatively adapts the well-established, high-shear dispersive mixing action of a twin screw mechanism. The distribution of particles and properties of composites are quantitatively evaluated. The adopted rheo process significantly improved the distribution of the reinforcement in the matrix with a strong interfacial bond between the two. A good combination of improved ultimate tensile strength (UTS) and tensile elongation (e) is obtained compared with composites produced by conventional processes.EPSR

Onderzoek ten behoeve van het herstel en beheer van Nederlandse laagveenwateren; eindrapportage 2003-2006

Dit rapport presenteert de resultaten en conclusies van het onderzoek aan laagveenwateren binnen het kader van het Overlevingsplan Bos en Natuur in de eerste fase (obn, 2003-2006). In Hoofdstuk 3 wordt een overzicht gegeven van de onderzoekslocaties. Vervolgens worden in Hoofdstuk 4 de belangrijkste bevindingen van het correlatieve onderzoek naar de samenhang tusen biodiversiteit en milieukwaliteit gepresenteerd, met in Hoofdstuk 5 de rol van hydrologie in het laagveenlandschap. In de daaropvolgende hoofdstukken 6 tot en met 10 staan de onderzoeksvragen, methoden, resultaten en conclusies van de verschillende deelonderzoeken weergegeven met betrekking tot visstandsbeheer (Hoofdstuk 6), water- en veenkwaliteit (Hoofdstuk 7), verlanding en veenvorming (Hoofdstuk 8), voedselwebrelaties (Hoofdstuk 9) en fauna (Hoofdstuk 10). Ten slotte worden in Hoofdstuk 11 de belangrijkste conclusies van het onderzoek in de eerste fase samengebracht en bediscussieerd, in relatie tot de directe betekenis voor het laagveenbeheer. Dit zal uitgewerkt worden aan de hand van de nieuw gegenereerde kennis en bestaande literatuur over de betreffende milieuproblemen (‘ver’-thema’s), en de voor- en nadelen van beschikbare OBN-maatregelen. Als afsluiting wordt aan de hand van de resultaten in fase 1 aangegeven welke onderzoeksvragen geprioriteerd zijn voor de tweede fas

Epilepsy, anti-seizure medication, intellectual disability and challenging behaviour – Everyone’s business, no one’s priority

Purpose People with Intellectual Disability (ID) and epilepsy are more likely to experience psychiatric conditions, challenging behaviour (CB), treatment resistance and adverse effects of anti-seizure medications (ASM) than those without. This population receives care from various professionals, depending on local care pathways. This study evaluates the training status, confidence, reported assessment and management practices of different professional groups involved in caring for people with ID, epilepsy and CB. Methods A cross sectional survey using a questionnaire developed by expert consensus which measured self-reported training status, confidence, and approaches to assessment and management of CB in people with ID and epilepsy was distributed to practitioners involved in epilepsy and/or ID. Results Of the 83 respondents, the majority had either a psychiatry/ID (n = 39), or Neurology/epileptology background (n = 31). Psychiatry/ID and Neurology/epileptology had similar confidence in assessing CB in ID-epilepsy cases, but Psychiatry/ID exhibited higher self-rated confidence in the management of these cases. While assessing and managing CB, Psychiatry/ID appeared more likely to consider mental health aspects, while Neurology/epileptology typically focused on ASM. Conclusion Psychiatry/ID and Neurology/epileptology professionals had varying training levels in epilepsy, ID and CB, had differing confidence levels in managing this patient population, and considered different factors when approaching assessment and management. As such, training opportunities in ID should be offered to neurology professionals, and vice versa. Based on the findings, a best practice checklist is presented, which aims to provide clinicians with a structured framework to consider causal explanations for CB in this population