237 resultados para Persistent robot navigation


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Purpose – The purpose of this paper is to describe an innovative compliance control architecture for hybrid multi‐legged robots. The approach was verified on the hybrid legged‐wheeled robot ASGUARD, which was inspired by quadruped animals. The adaptive compliance controller allows the system to cope with a variety of stairs, very rough terrain, and is also able to move with high velocity on flat ground without changing the control parameters. Design/methodology/approach – The paper shows how this adaptivity results in a versatile controller for hybrid legged‐wheeled robots. For the locomotion control we use an adaptive model of motion pattern generators. The control approach takes into account the proprioceptive information of the torques, which are applied on the legs. The controller itself is embedded on a FPGA‐based, custom designed motor control board. An additional proprioceptive inclination feedback is used to make the same controller more robust in terms of stair‐climbing capabilities. Findings – The robot is well suited for disaster mitigation as well as for urban search and rescue missions, where it is often necessary to place sensors or cameras into dangerous or inaccessible areas to get a better situation awareness for the rescue personnel, before they enter a possibly dangerous area. A rugged, waterproof and dust‐proof corpus and the ability to swim are additional features of the robot. Originality/value – Contrary to existing approaches, a pre‐defined walking pattern for stair‐climbing was not used, but an adaptive approach based only on internal sensor information. In contrast to many other walking pattern based robots, the direct proprioceptive feedback was used in order to modify the internal control loop, thus adapting the compliance of each leg on‐line.

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The inspection of marine vessels is currently performed manually. Inspectors use tools (e.g. cameras and devices for non-destructive testing) to detect damaged areas, cracks, and corrosion in large cargo holds, tanks, and other parts of a ship. Due to the size and complex geometry of most ships, ship inspection is time-consuming and expensive. The EU-funded project INCASS develops concepts for a marine inspection robotic assistant system to improve and automate ship inspections. In this paper, we introduce our magnetic wall–climbing robot: Marine Inspection Robotic Assistant (MIRA). This semiautonomous lightweight system is able to climb a vessels steel frame to deliver on-line visual inspection data. In addition, we describe the design of the robot and its building subsystems as well as its hardware and software components.

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For future planetary robot missions, multi-robot-systems can be considered as a suitable platform to perform space mission faster and more reliable. In heterogeneous robot teams, each robot can have different abilities and sensor equipment. In this paper we describe a lunar demonstration scenario where a team of mobile robots explores an unknown area and identifies a set of objects belonging to a lunar infrastructure. Our robot team consists of two exploring scout robots and a mobile manipulator. The mission goal is to locate the objects within a certain area, to identify the objects, and to transport the objects to a base station. The robots have a different sensor setup and different capabilities. In order to classify parts of the lunar infrastructure, the robots have to share the knowledge about the objects. Based on the different sensing capabilities, several information modalities have to be shared and combined by the robots. In this work we propose an approach using spatial features and a fuzzy logic based reasoning for distributed object classification.

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In contrast to single robotic agent, multi-robot systems are highly dependent on reliable communication. Robots have to synchronize tasks or to share poses and sensor readings with other agents, especially for co-operative mapping task where local sensor readings are incorporated into a global map. The drawback of existing communication frameworks is that most are based on a central component which has to be constantly within reach. Additionally, they do not prevent data loss between robots if a failure occurs in the communication link. During a distributed mapping task, loss of data is critical because it will corrupt the global map. In this work, we propose a cloud-based publish/subscribe mechanism which enables reliable communication between agents during a cooperative mission using the Data Distribution Service (DDS) as a transport layer. The usability of our approach is verified by several experiments taking into account complete temporary communication loss.

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Currently, the inspection of sea-going vessels is performed manually. Ship surveyors do a visual inspection; in some cases they also use cameras and non-destructive testing methods. Prior to a ship surveying process a lot of scaffolding has to be provided in order to make every spot accessible for the surveyor. In this work a robotic system is presented, which is able to access many areas of a cargo hold of a ship and perform visual inspection without any scaffolding. The paper also describes how the position of the acquired data is estimated with an optical 3D tracking unit and how critical points on the hull can be marked via a remote controlled marker device. Furthermore first results of onboard tests with the system are provided.

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The International Journal of Robotics Research (IJRR) has a long history of publishing the state-of-the-art in the field of robotic vision. This is the fourth special issue devoted to the topic. Previous special issues were published in 2012 (Volume 31, No. 4), 2010 (Volume 29, Nos 2–3) and 2007 (Volume 26, No. 7, jointly with the International Journal of Computer Vision). In a closely related field was the special issue on Visual Servoing published in IJRR, 2003 (Volume 22, Nos 10–11). These issues nicely summarize the highlights and progress of the past 12 years of research devoted to the use of visual perception for robotics.

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PURPOSE Brivanib, an oral, multi-targeted tyrosine kinase inhibitor with activity against vascular endothelial growth factor (VEGF) and fibroblast growth factor receptor (FGFR) was investigated as a single agent in a phase II trial to assess the activity and tolerability in recurrent or persistent endometrial cancer (EMC). PATIENTS AND METHODS Eligible patients had persistent or recurrent EMC after receiving one to two prior cytotoxic regimens, measurable disease, and performance status of ≤2. Treatment consisted of brivanib 800 mg orally every day until disease progression or prohibitive toxicity. Primary endpoints were progression-free survival (PFS) at six months and objective tumor response. Expression of multiple angiogenic proteins and FGFR2 mutation status was assessed. RESULTS Forty-five patients were enrolled. Forty-three patients were eligible and evaluable. Median age was 64 years. Twenty-four patients (55.8%) received prior radiation. Median number of cycles was two (range 1-24). No GI perforations but one rectal fistula were seen. Nine patients had grade 3 hypertension, with one experiencing grade 4 confusion. Eight patients (18.6%; 90% CI 9.6%-31.7%) had responses (one CR and seven PRs), and 13 patients (30.2%; 90% CI 18.9%-43.9%) were PFS at six months. Median PFS and overall survival (OS) were 3.3 and 10.7 months, respectively. When modeled jointly, VEGF and angiopoietin-2 expression may diametrically predict PFS. Estrogen receptor-α (ER) expression was positively correlated with OS. CONCLUSION Brivanib is reasonably well tolerated and worthy of further investigation based on PFS at six months in recurrent or persistent EMC.

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Introduction: Training for and competing in ultraendurance exercise events is associated with an improvement in endogenous antioxidant defenses as well as increased oxidative stress. However, consequences on health are currently unclear. Purpose: We aimed to examine the impact of training- and acute exercise-induced changes in the antioxidant capacity on the oxidant/antioxidant balance after an ironman triathlon and whether there are indications for sustained oxidative damage. Methods: Blood samples were taken from 42 well-trained male triathletes 2 d before an ironman triathlon, then immediately postrace, 1, 5, and 19 d later. Blood was analyzed for conjugated dienes (CD), malondialdehyde (MDA), oxidized low-density lipoprotein (oxLDL), oxLDL:LDL ratio, advanced oxidation protein products (AOPP), AOPP:total protein (TP) ratio, Trolox equivalent antioxidant capacity (TEAC), uric acid (UA) in plasma, and activities of superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), and catalase (CAT) in erythrocytes. Results: Immediately postrace, there were significant increases in CD, AOPP, TEAC, UA (for all P < 0.001), and AOPP:TP (P < 0.01). MDA rose significantly (P < 0.01) 1 d postrace, whereas CD (P < 0.01), AOPP (P = 0.01), AOPP:TP (P < 0.05), and TEAC (P < 0.001) remained elevated. OxLDL:LDL trended to increase, whereas oxLDL significantly (P < 0.01) decreased 1 d postrace. Except for GSH-Px (P = 0.08), activities of SOD (P < 0.001) and CAT (P < 0.05) significantly decreased postrace. All oxidative stress markers had returned to prerace values 5 d postrace. Furthermore, several relationships between training status and oxidative stress markers, TEAC, and antioxidant enzyme activities were noted. Conclusions: This study indicates that despite a temporary increase in most (but not all) oxidative stress markers, there is no persistent oxidative stress in response to an ironman triathlon, probably due to training- and exercise-induced protective alterations in the antioxidant defense system.

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During acute and strenuous exercise, the enhanced formation of reactive oxygen species can induce damage to lipids, proteins, and nucleic acids. The aim of this study was to investigate the effect of an Ironman triathlon (3.8 km swim, 180 km cycle, 42 km run), as a prototype of ultra-endurance exercise, on DNA stability. As biomarkers of genomic instability, the number of micronuclei, nucleoplasmic bridges, and nuclear buds were measured within the cytokinesis-block micronucleus cytome assay in once-divided peripheral lymphocytes of 20 male triathletes. Blood samples were taken 2 days before, within 20 min after the race, and 5 and 19 days post-race. Overall, the number of micronuclei decreased (P < 0.05) after the race, remained at a low level until 5 days post-race, and declined further to 19 days post-race (P < 0.01). The frequency of nucleoplasmic bridges and nuclear buds did not change immediately after the triathlon. The number of nucleoplasmic bridge declined from 2 days pre-race to 19 days post-exercise (P < 0.05). The frequency of nuclear buds increased after the triathlon, peaking 5 days post-race (P < 0.01) and decreased to basic levels 19 days after the race (P < 0.01). The results suggest that an Ironman triathlon does not cause long-lasting DNA damage in well-trained athletes.

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A 60-year-old male experienced a marked unilateral myopic shift of 20 D following attempted removal of intravitreal heavy silicone oil (HSO) used in the treatment of inferior proliferative vitreous retinopathy following retinal detachment. Examination revealed HSO adherent to the corneal endothelium forming a convex interface with the aqueous, obscuring the entire pupil, which required surgical intervention to restore visual acuity. This case highlights the potential ocular complications associated with silicone oil migration into the anterior chamber, which include corneal endothelial decompensation and a significant increase in myopia.

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Particle swarm optimization (PSO), a new population based algorithm, has recently been used on multi-robot systems. Although this algorithm is applied to solve many optimization problems as well as multi-robot systems, it has some drawbacks when it is applied on multi-robot search systems to find a target in a search space containing big static obstacles. One of these defects is premature convergence. This means that one of the properties of basic PSO is that when particles are spread in a search space, as time increases they tend to converge in a small area. This shortcoming is also evident on a multi-robot search system, particularly when there are big static obstacles in the search space that prevent the robots from finding the target easily; therefore, as time increases, based on this property they converge to a small area that may not contain the target and become entrapped in that area.Another shortcoming is that basic PSO cannot guarantee the global convergence of the algorithm. In other words, initially particles explore different areas, but in some cases they are not good at exploiting promising areas, which will increase the search time.This study proposes a method based on the particle swarm optimization (PSO) technique on a multi-robot system to find a target in a search space containing big static obstacles. This method is not only able to overcome the premature convergence problem but also establishes an efficient balance between exploration and exploitation and guarantees global convergence, reducing the search time by combining with a local search method, such as A-star.To validate the effectiveness and usefulness of algorithms,a simulation environment has been developed for conducting simulation-based experiments in different scenarios and for reporting experimental results. These experimental results have demonstrated that the proposed method is able to overcome the premature convergence problem and guarantee global convergence.

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This paper presents a visual SLAM method for temporary satellite dropout navigation, here applied on fixed- wing aircraft. It is designed for flight altitudes beyond typical stereo ranges, but within the range of distance measurement sensors. The proposed visual SLAM method consists of a common localization step with monocular camera resectioning, and a mapping step which incorporates radar altimeter data for absolute scale estimation. With that, there will be no scale drift of the map and the estimated flight path. The method does not require simplifications like known landmarks and it is thus suitable for unknown and nearly arbitrary terrain. The method is tested with sensor datasets from a manned Cessna 172 aircraft. With 5% absolute scale error from radar measurements causing approximately 2-6% accumulation error over the flown distance, stable positioning is achieved over several minutes of flight time. The main limitations are flight altitudes above the radar range of 750 m where the monocular method will suffer from scale drift, and, depending on the flight speed, flights below 50 m where image processing gets difficult with a downwards-looking camera due to the high optical flow rates and the low image overlap.

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This paper presents an unmanned aircraft system (UAS) that uses a probabilistic model for autonomous front-on environmental sensing or photography of a target. The system is based on low-cost and readily-available sensor systems in dynamic environments and with the general intent of improving the capabilities of dynamic waypoint-based navigation systems for a low-cost UAS. The behavioural dynamics of target movement for the design of a Kalman filter and Markov model-based prediction algorithm are included. Geometrical concepts and the Haversine formula are applied to the maximum likelihood case in order to make a prediction regarding a future state of a target, thus delivering a new waypoint for autonomous navigation. The results of the application to aerial filming with low-cost UAS are presented, achieving the desired goal of maintained front-on perspective without significant constraint to the route or pace of target movement.

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A nation-wide passive air sampling campaign recorded concentrations of persistent organic pollutants in Australia's atmosphere in 2012. XAD-based passive air samplers were deployed for one year at 15 sampling sites located in remote/background, agricultural and semi-urban and urban areas across the continent. Concentrations of 47 polychlorinated biphenyls ranged from 0.73 to 72 pg m-3 (median of 8.9 pg m-3) and were consistently higher at urban sites. The toxic equivalent concentration for the sum of 12 dioxin-like PCBs was low, ranging from below detection limits to 0.24 fg m-3 (median of 0.0086 fg m-3). Overall, the levels of polychlorinated biphenyls in Australia were among the lowest reported globally to date. Among the organochlorine pesticides, hexachlorobenzene had the highest (median of 41 pg m-3) and most uniform concentration (with a ratio between highest and lowest value [similar]5). Bushfires may be responsible for atmospheric hexachlorobenzene levels in Australia that exceeded Southern Hemispheric baseline levels by a factor of [similar]4. Organochlorine pesticide concentrations generally increased from remote/background and agricultural sites to urban sites, except for high concentrations of [small alpha]-endosulfan and DDTs at specific agricultural sites. Concentrations of heptachlor (0.47-210 pg m-3), dieldrin (ND-160 pg m-3) and trans- and cis-chlordanes (0.83-180 pg m-3, sum of) in Australian air were among the highest reported globally to date, whereas those of DDT and its metabolites (ND-160 pg m-3, sum of), [small alpha]-, [small beta]-, [gamma]- and [small delta]-hexachlorocyclohexane (ND-6.7 pg m-3, sum of) and [small alpha]-endosulfan (ND-27 pg m-3) were among the lowest.

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Robot Path Planning (RPP) in dynamic environments is a search problem based on the examination of collision-free paths in the presence of dynamic and static obstacles. Many techniques have been developed to solve this problem. Trapping in a local minima and maintaining a Real-Time performance are known as the two most important challenges that these techniques face to solve such problem. This study presents a comprehensive survey of the various techniques that have been proposed in this domain. As part of this survey, we include a classification of the approaches and identify their methods.