18,568 research outputs found
Towards a Formal Verification Methodology for Collective Robotic Systems
We introduce a UML-based notation for graphically modeling
systems’ security aspects in a simple and intuitive
way and a model-driven process that transforms graphical
specifications of access control policies in XACML. These
XACML policies are then translated in FACPL, a policy
language with a formal semantics, and the resulting policies
are evaluated by means of a Java-based software tool
Accurate robot simulation
Robot simulators are valuable tools for researchers
to develop control code in a fast and efficient manner without spending time setting up physical experiments. Most simulators, however, do not model the real world accurately. As a consequence, when a program is run on a real robot it may behave differently from when run in simulation. In this paper we present a method of developing
a robot simulator that models the operation of a real robot in a real environment accurately, using real robot data and system identification to construct the simulator's model
Accurate robot simulation through system identification
Robot simulators are useful tools for developing robot behaviours. They provide a fast and efficient means to test robot control code at the convenience of the office
desk. In all but the simplest cases though, due to the complexities of the physical systems modelled in the simulator, there are considerable differences between the
behaviour of the robot in the simulator and that in the real world environment. In this paper we present a novel method to create a robot simulator using real sensor data. Logged sensor data is used to construct a mathematically explicit model(in the form of a NARMAX polynomial) of the robot’s environment. The advantage of such a transparent model — in contrast to opaque modelling methods such as
artificial neural networks — is that it can be analysed to characterise the modelled system, using established mathematical methods In this paper we compare the behaviour of the robot running a particular task in
both the simulator and the real-world using qualitative and quantitative measures including statistical methods to investigate the faithfulness of the simulator
Towards Odor-Sensitive Mobile Robots
J. Monroy, J. Gonzalez-Jimenez, "Towards Odor-Sensitive Mobile Robots", Electronic Nose Technologies and Advances in Machine Olfaction, IGI Global, pp. 244--263, 2018, doi:10.4018/978-1-5225-3862-2.ch012
Versión preprint, con permiso del editorOut of all the components of a mobile robot, its sensorial system is undoubtedly among the most critical
ones when operating in real environments. Until now, these sensorial systems mostly relied on range
sensors (laser scanner, sonar, active triangulation) and cameras. While electronic noses have barely
been employed, they can provide a complementary sensory information, vital for some applications, as
with humans. This chapter analyzes the motivation of providing a robot with gas-sensing capabilities
and also reviews some of the hurdles that are preventing smell from achieving the importance of other
sensing modalities in robotics. The achievements made so far are reviewed to illustrate the current status
on the three main fields within robotics olfaction: the classification of volatile substances, the spatial
estimation of the gas dispersion from sparse measurements, and the localization of the gas source within
a known environment
Comparing robot controllers through system identification
In the mobile robotics field, it is very common to find different control programs designed to achieve a particular robot task. Although there are many ways to evaluate these controllers qualitatively, there is a lack of formal methodology to compare them from a mathematical point of view. In this paper we present a novel approach to compare robot control codes quantitatively based on system identification: Initially the transparent mathematical models of the controllers are obtained using the NARMAX system identification process. Then we use these models to analyse the general characteristics of the cotrollers from a mathematical point of view. In this way, we are able to compare different control programs objectively based on quantitative measures. We demonstrate our approach by comparing two different robot control programs, which were designed to drive the robot through door-like openings
Evolution of Swarm Robotics Systems with Novelty Search
Novelty search is a recent artificial evolution technique that challenges
traditional evolutionary approaches. In novelty search, solutions are rewarded
based on their novelty, rather than their quality with respect to a predefined
objective. The lack of a predefined objective precludes premature convergence
caused by a deceptive fitness function. In this paper, we apply novelty search
combined with NEAT to the evolution of neural controllers for homogeneous
swarms of robots. Our empirical study is conducted in simulation, and we use a
common swarm robotics task - aggregation, and a more challenging task - sharing
of an energy recharging station. Our results show that novelty search is
unaffected by deception, is notably effective in bootstrapping the evolution,
can find solutions with lower complexity than fitness-based evolution, and can
find a broad diversity of solutions for the same task. Even in non-deceptive
setups, novelty search achieves solution qualities similar to those obtained in
traditional fitness-based evolution. Our study also encompasses variants of
novelty search that work in concert with fitness-based evolution to combine the
exploratory character of novelty search with the exploitatory character of
objective-based evolution. We show that these variants can further improve the
performance of novelty search. Overall, our study shows that novelty search is
a promising alternative for the evolution of controllers for robotic swarms.Comment: To appear in Swarm Intelligence (2013), ANTS Special Issue. The final
publication will be available at link.springer.co
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