Monthly Archives: June 2017

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Combination of several mobile robot localization methods in order to achieve high accuracy in industrial environments, with interesting figures for current localization accuracy achievable by standard solutions

June 8, 2017 12:23 ,

Goran Vasiljevi, Damjan Mikli, Ivica Draganjac, Zdenko Kovai, Paolo Lista, High-accuracy vehicle localization for autonomous warehousing, Robotics and Computer-Integrated Manufacturing, Volume 42, December 2016, Pages 1-16, ISSN 0736-5845, DOI: 10.1016/j.rcim.2016.05.001.

The research presented in this paper aims to bridge the gap between the latest scientific advances in autonomous vehicle localization and the industrial state of the art in autonomous warehousing. Notwithstanding great scientific progress in the past decades, industrial autonomous warehousing systems still rely on external infrastructure for obtaining their precise location. This approach increases warehouse installation costs and decreases system reliability, as it is sensitive to measurement outliers and the external localization infrastructure can get dirty or damaged. Several approaches, well studied in scientific literature, are capable of determining vehicle position based only on information provided by on board sensors, most commonly wheel encoders and laser scanners. However, scientific results published to date either do not provide sufficient accuracy for industrial applications, or have not been extensively tested in realistic, industrial-like operating conditions. In this paper, we combine several well established algorithms into a high-precision localization pipeline, capable of computing the pose of an autonomous forklift to sub-centimeter precision. The algorithms use only odometry information from wheel encoders and range readings from an on board laser scanner. The effectiveness of the proposed solution is evaluated by an extensive experiment that lasted for several days, and was performed in a realistic industrial-like environment.

Posted in: Mobile Robot Localization , Tagged: ,

On how the calculus of utility of actions drives many human behaviours

June 8, 2017 12:11 ,

Julian Jara-Ettinger, Hyowon Gweon, Laura E. Schulz, Joshua B. Tenenbaum, The Naïve Utility Calculus: Computational Principles Underlying Commonsense Psychology, Trends in Cognitive Sciences, Volume 20, Issue 8, 2016, Pages 589-604, ISSN 1364-6613, DOI: 10.1016/j.tics.2016.05.011.

We propose that human social cognition is structured around a basic understanding of ourselves and others as intuitive utility maximizers: from a young age, humans implicitly assume that agents choose goals and actions to maximize the rewards they expect to obtain relative to the costs they expect to incur. This \u2018naïve utility calculus\u2019 allows both children and adults observe the behavior of others and infer their beliefs and desires, their longer-term knowledge and preferences, and even their character: who is knowledgeable or competent, who is praiseworthy or blameworthy, who is friendly, indifferent, or an enemy. We review studies providing support for the naïve utility calculus, and we show how it captures much of the rich social reasoning humans engage in from infancy.

Posted in: Psycho-physiological bases of engineering , Tagged:

Evidences that the brain encodes numbers on an internal continous line and that the zero value is also represented

June 8, 2017 12:07 ,

Luca Rinaldi, Luisa Girelli, A Place for Zero in the Brain, Trends in Cognitive Sciences, Volume 20, Issue 8, 2016, Pages 563-564, ISSN 1364-6613, DOI: 10.1016/j.tics.2016.06.006.

It has long been thought that the primary cognitive and neural systems responsible for processing numerosities are not predisposed to encode empty sets (i.e., numerosity zero). A new study challenges this view by demonstrating that zero is translated into an abstract quantity along the numerical continuum by the primate parietofrontal magnitude system.

Posted in: Psycho-physiological bases of engineering , Tagged:

Value iteration applied to continuous LTI systems control

June 8, 2017 11:19 ,

Tao Bian, Zhong-Ping Jiang, Value iteration and adaptive dynamic programming for data-driven adaptive optimal control design, Automatica, Volume 71, September 2016, Pages 348-360, ISSN 0005-1098, DOI: 10.1016/j.automatica.2016.05.003.

This paper presents a novel non-model-based, data-driven adaptive optimal controller design for linear continuous-time systems with completely unknown dynamics. Inspired by the stochastic approximation theory, a continuous-time version of the traditional value iteration (VI) algorithm is presented with rigorous convergence analysis. This VI method is crucial for developing new adaptive dynamic programming methods to solve the adaptive optimal control problem and the stochastic robust optimal control problem for linear continuous-time systems. Fundamentally different from existing results, the a priori knowledge of an initial admissible control policy is no longer required. The efficacy of the proposed methodology is illustrated by two examples and a brief comparative study between VI and earlier policy-iteration methods.

Posted in: Control Engineering , Tagged:

A variant of particle filters that uses feedback to model how particles move towards the real posterior

June 8, 2017 11:17 ,

T. Yang, P.~G. Mehta, S.~P. Meyn, Feedback particle filter, IEEE Transactions on Automatic Control, 58 (10) (2013), pp. 2465â–2480, DOI: 10.1109/TAC.2013.2258825.

The feedback particle filter introduced in this paper is a new approach to approximate nonlinear filtering, motivated by techniques from mean-field game theory. The filter is defined by an ensemble of controlled stochastic systems (the particles). Each particle evolves under feedback control based on its own state, and features of the empirical distribution of the ensemble. The feedback control law is obtained as the solution to an optimal control problem, in which the optimization criterion is the Kullback-Leibler divergence between the actual posterior, and the common posterior of any particle. The following conclusions are obtained for diffusions with continuous observations: 1) The optimal control solution is exact: The two posteriors match exactly, provided they are initialized with identical priors. 2) The optimal filter admits an innovation error-based gain feedback structure. 3) The optimal feedback gain is obtained via a solution of an Euler-Lagrange boundary value problem; the feedback gain equals the Kalman gain in the linear Gaussian case. Numerical algorithms are introduced and implemented in two general examples, and a neuroscience application involving coupled oscillators. In some cases it is found that the filter exhibits significantly lower variance when compared to the bootstrap particle filter.

Posted in: Bayesian filtering , Tagged:

Integration of the ICP algorithm with a Kalman filter to improve relative localization, with a good state-of-the-art of ICP algorithms

June 8, 2017 11:07 ,

F. Aghili and C. Y. Su, “Robust Relative Navigation by Integration of ICP and Adaptive Kalman Filter Using Laser Scanner and IMU,” in IEEE/ASME Transactions on Mechatronics, vol. 21, no. 4, pp. 2015-2026, Aug. 2016.DOI: 10.1109/TMECH.2016.2547905.

This paper presents a robust six-degree-of-freedom relative navigation by combining the iterative closet point (ICP) registration algorithm and a noise-adaptive Kalman filter in a closed-loop configuration together with measurements from a laser scanner and an inertial measurement unit (IMU). In this approach, the fine-alignment phase of the registration is integrated with the filter innovation step for estimation correction, while the filter estimate propagation provides the coarse alignment needed to find the corresponding points at the beginning of ICP iteration cycle. The convergence of the ICP point matching is monitored by a fault-detection logic, and the covariance associated with the ICP alignment error is estimated by a recursive algorithm. This ICP enhancement has proven to improve robustness and accuracy of the pose-tracking performance and to automatically recover correct alignment whenever the tracking is lost. The Kalman filter estimator is designed so as to identify the required parameters such as IMU biases and location of the spacecraft center of mass. The robustness and accuracy of the relative navigation algorithm is demonstrated through a hardware-in-the loop simulation setting, in which actual vision data for the relative navigation are generated by a laser range finder scanning a spacecraft mockup attached to a robotic motion simulator.

Posted in: Mobile Robot Localization , Tagged: ,

Massive parallelization of POMDPs with a very good state-of-the-art review

June 8, 2017 10:44 ,

Taekhee Lee, Young J. Kim (2015), Massively parallel motion planning algorithms under uncertainty using POMDP , The International Journal of Robotics Research, Vol 35, Issue 8, pp. 928 – 942, DOI: 10.1177/0278364915594856.

We present new parallel algorithms that solve continuous-state partially observable Markov decision process (POMDP) problems using the GPU (gPOMDP) and a hybrid of the GPU and CPU (hPOMDP). We choose the Monte Carlo value iteration (MCVI) method as our base algorithm and parallelize this algorithm using the multi-level parallel formulation of MCVI. For each parallel level, we propose efficient algorithms to utilize the massive data parallelism available on modern GPUs. Our GPU-based method uses the two workload distribution techniques, compute/data interleaving and workload balancing, in order to obtain the maximum parallel performance at the highest level. Here we also present a CPU–GPU hybrid method that takes advantage of both CPU and GPU parallelism in order to solve highly complex POMDP planning problems. The CPU is responsible for data preparation, while the GPU performs Monte Cacrlo simulations; these operations are performed concurrently using the compute/data overlap technique between the CPU and GPU. To the best of the authors’ knowledge, our algorithms are the first parallel algorithms that efficiently execute POMDP in a massively parallel fashion utilizing the GPU or a hybrid of the GPU and CPU. Our algorithms outperform the existing CPU-based algorithm by a factor of 75–99 based on the chosen benchmark.

Posted in: Robotic software , Tagged:

Combining efficiently symbolic planning with geometric planning

June 8, 2017 10:41 ,

Fabien Lagriffoul, Benjamin Andres (2016), Combining task and motion planning: A culprit detection problem , The International Journal of Robotics Research, Vol 35, Issue 8, pp. 890 – 927, DOI: 10.1177/0278364915619022.

Solving problems combining task and motion planning requires searching across a symbolic search space and a geometric search space. Because of the semantic gap between symbolic and geometric representations, symbolic sequences of actions are not guaranteed to be geometrically feasible. This compels us to search in the combined search space, in which frequent backtracks between symbolic and geometric levels make the search inefficient. We address this problem by guiding symbolic search with rich information extracted from the geometric level through culprit detection mechanisms.

Posted in: Robot motion planning, Robot task planning , Tagged:

A novel clock synchronization architecture for networked systems based on forcing the synchronization, with a nice summary of uses of clock synchronization and of existing synchronization architectures

June 8, 2017 10:13 ,

S. Bolognani, R. Carli, E. Lovisari and S. Zampieri, “A Randomized Linear Algorithm for Clock Synchronization in Multi-Agent Systems,” in IEEE Transactions on Automatic Control, vol. 61, no. 7, pp. 1711-1726, July 2016. DOI: 10.1109/TAC.2015.2479136.

A broad family of randomized clock synchronization protocols based on a second order consensus algorithm is proposed. Under mild conditions on the graph connectivity, it is proved that the parameters of the algorithm can always be tuned in such a way that the clock synchronization is achieved in the probabilistic mean-square sense. This family of algorithms contains, as particular cases, several known approaches which range from distributed asynchronous to hierarchical synchronous protocols. This is illustrated by specializing the algorithm for the well-known broadcast and gossip scenarios in wireless communications, and for the standard hierarchical protocol used in the context of wired communications in data networks. In these cases, we show how the feasible range for the algorithm parameters can be explicitly computed. Finally, the performance of this strategy is validated by actual implementation in a real testbed and by numerical simulations.

Posted in: Communication networks , Tagged:

Interesting approach for communicating robots: through the passive recognition of others patterns of motion

June 8, 2017 09:38 ,

Barnali Das, Micael S. Couceiro, Patricia A. Vargas, MRoCS: A new multi-robot communication system based on passive action recognition, Robotics and Autonomous Systems, Volume 82, August 2016, Pages 46-60, ISSN 0921-8890, DOI: 10.1016/j.robot.2016.04.002.

Multi-robot search-and-rescue missions often face major challenges in adverse environments due to the limitations of traditional implicit and explicit communication. This paper proposes a novel multi-robot communication system (MRoCS), which uses a passive action recognition technique that overcomes the shortcomings of traditional models. The proposed MRoCS relies on individual motion, by mimicking the waggle dance of honey bees and thus forming and recognising different patterns accordingly. The system was successfully designed and implemented in simulation and with real robots. Experimental results show that, the pattern recognition process successfully reported high sensitivity with good precision in all cases for three different patterns thus corroborating our hypothesis.

Posted in: Robotics , Tagged: ,