Suchergebnisse

Pose SLAM is the variant of simultaneous localization and map building (SLAM) is the variant of SLAM, in which only the robot trajectory is estimated and where landmarks are only used to produce relative constraints between robot poses. To reduce the computational cost of the information filter form of Pose SLAM and, at the same time, to delay inconsistency as much as possible, we introduce an approach that takes into account only highly informative loop-closure links and nonredundant poses. This approach includes constant time procedures to compute the distance between poses, the expected information gain for each potential link, and the exact marginal covariances while moving in open loop, as well as a procedure to recover the state after a loop closure that, in practical situations, scales linearly in terms of both time and memory. Using these procedures, the robot operates most of the time in open loop, and the cost of the loop closure is amortized over long trajectories. This way, the computational bottleneck shifts to data association, which is the search over the set of previously visited poses to determine good candidates for sensor registration. To speed up data association, we introduce a method to search for neighboring poses whose complexity ranges from logarithmic in the usual case to linear in degenerate situations. The method is based on organizing the pose information in a balanced tree whose internal levels are defined using interval arithmetic. The proposed Pose-SLAM approach is validated through simulations, real mapping sessions, and experiments using standard SLAM data sets. ; This work was supported by projects: 'Ubiquitous networking robotics in urban settings' (E-00938), 'Analysis and motion planning of complex robotic systems' (4802), 'CONSOLIDER-INGENIO 2010 Multimodal interaction in pattern recognition and computer vision' (V-00069), 'Percepción y acción ante incertidumbre' (4803). This work was supported by Project DPI-2007-60858, Project DPI-2008-06022, Project Multimodal Interaction in Pattern Recognition and Computer Vision Consolider-Ingenio 2010, and by the European Union Ubiquitous Networking Robotics in Urban Settings under Project IST-FP6-STREP-045062. The work of V. Ila was supported in part by the Spanish Ministry of Science and Innovation under a Juan de la Cierva Postdoctoral Fellowship. ; Peer Reviewed

We propose a novel approach to optimize Partially Observable Markov Decisions Processes (POMDPs) defined on continuous spaces. To date, most algorithms for model-based POMDPs are restricted to discrete states, actions, and observations, but many real-world problems such as, for instance, robot navigation, are naturally defined on continuous spaces. In this work, we demonstrate that the value function for continuous POMDPs is convex in the beliefs over continuous state spaces, and piecewise-linear convex for the particular case of discrete observations and actions but still continuous states. We also demonstrate that continuous Bellman backups are contracting and isotonic ensuring the monotonic convergence of value-iteration algorithms. Relying on those properties, we extend the PERSEUS algorithm, originally developed for discrete POMDPs, to work in continuous state spaces by representing the observation, transition, and reward models using Gaussian mixtures, and the beliefs using Gaussian mixtures or particle sets. With these representations, the integrals that appear in the Bellman backup can be computed in closed form and, therefore, the algorithm is computationally feasible. Finally, we further extend PERSEUS to deal with continuous action and observation sets by designing effective sampling approaches. ; This work was supported by the project 'Perception, action & cognition through learning of object-action complexes.' (4915). Josep M. Porta has been partially supported by a Ramón y Cajal contract from the Spanish government and by the EU PACO-PLUS Project FP6-2004-IST-4-27657. Nikos Vlassis and Matthijs Spaan are supported by PROGRESS, the embedded systems research program of the Dutch organization for Scientific Research NWO, the Dutch Ministry of Economic Affairs and the Technology Foundation STW, project AES5414. Pascal Poupart is supported by the Canada's National Science and Engineering Research Council. ; Peer Reviewed

Occupational, accidental, or suicidal exposure to acrylamide (ACR) may result in a neurotoxic syndrome. Development of animal models of acrylamide neurotoxicity is necessary for increasing our mechanistic understanding of this syndrome and developing more effective therapies. A new model for acute ACR neurotoxicity has been recently developed in adult zebrafish. Whereas the results of the initial characterization were really promising, a further characterization is needed for testing the construct validity of the model. In this study, the presence of gait abnormalities has been investigated by using ZebraGait, software specifically designed to analyze the kinematics of fish swimming in a water tunnel. The results of the kinematic analyses demonstrated that the model exhibits mild-to-moderate gait abnormalities. Moreover, the model exhibited negative scototaxis, a result confirming a phenotype of anxiety comorbid with depression phenotype. Interestingly, depletion of the reduced glutathione levels was found in the brain without a concomitant increase in oxidative stress. Finally, hypolocomotion and positive geotaxis exhibited by this model were fully recovered 5 days after transferring the fish to clean fish-water. All this data support the validity of the ACR acute neurotoxicity model developed in adult zebrafish. ; We thank Dr. Caio Maximino, from the Universidade Federal do Sul e Sudeste do Pará (Marabá, Brazil), for his comments and suggestions on the DLT. The IRI Lab technical staff members are gratefully thanked for their valuable assistance in the design of the experimental setup for video-recording the fish swimming. This work was supported by the NATO SfP project MD. SFPP 984777 (D.R.) and the Spanish Government (CTM2017-83242-R; D.R. and J.M.P.). M.F. acknowledges financial support from the Beatriu de Pinós programme (Grant No. 2016 BP 00233) provided by the Secretariat of Universities and Research department of the Ministry for Business and Knowledge, Catalonia Government. ; Peer reviewed

Fenitrothion is an organophosphorus insecticide usually found in aquatic ecosystems at concentrations in the range of low ng/L. In this manuscript we show that 24 h exposure to environmental concentrations of fenitrothion, from ng/L to low μg/L, altered basal locomotor activity, visual-motor response and acoustic/vibrational escape response of zebrafish larvae. Furthermore, fenitrothion and expression of gap43a, gfap, atp2b1a, and mbp exhibited a significant non-monotonic concentration-response relationship. Once determined that environmental concentrations of fenitrothion were neurotoxic for zebrafish larvae, a computational analysis identified potential protein targets of this compound. Some of the predictions, including interactions with acetylcholinesterase, monoamine-oxidases and androgen receptor (AR), were experimentally validated. Binding to AR was the most suitable candidate for molecular initiating event, as indicated by both the up-regulation of cyp19a1b and sult2st3 and the non-monotonic relationship found between fenitrothion and the observed responses. Finally, when the integrity of the monoaminergic system was evaluated, altered levels of L-DOPA, DOPAC, HVA and 5-HIAA were found, as well as a significant up-regulation of slc18a2 expression at the lowest concentrations of fenitrothion. These data strongly suggest that concentrations of fenitrothion commonly found in aquatic ecosystems present a significant environmental risk for fish communities. ; We thank Dr. Harold A. Burgess for providing Flote software package and advice with the kinematic analysis setup for the acoustic/vibrational evoked escape response. This work was supported by the Spanish Government with FEDER Funds (CTM2017-83242- R; D.R.) and the network of recognized research groups by the Catalan Government (2017 SGR_902). Melissa Faria acknowledges financial support from the Beatriu de Pinós programme (grant Nº: 2016 BP 00233) provided by the Secretariat of Universities and Research department of the Ministry for Business and Knowledge, Catalonia Government. Maria Pagano benefited from a PhD grant (Avviso 24/2018) given by Sicily region, supported by FSE 2014-2020. Mention of specific products or trade names does not indicate endorsement by the US federal government. ; Peer reviewed