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This paper studies the Lego NXT platform's suitability for evolutionary robotics. It is shown that the low-cost Lego NXT educational set is indeed adequate for simple experiments in evolutionary robotics. This is demonstrated by an experiment, where an artificial neural network-based controller capable of behaving meaningfully in a Lego sumo wrestling context is evolved on physical Lego NXT robots...
In this paper, we consider magnetic field SLAM exploration using a mobile robot with a magnetometer and wheel encoders. We propose computationally feasible solutions to model magnetic fields using frequency domain Gaussian processes. In addition, we propose a path planning algorithm to efficiently collect a given level of accuracy for magnetic field models. The path planning is based on partition...
This paper proposes a simple adaptive weight computing method for particle filters that utilizes knowledge about predictive model uncertainty. In each time step the particles are assigned into subsets based on the corresponding uncertainty estimates. The weights are then updated based on accumulated subset-inclusion and likelihood information using a discrete set of measurement likelihood functions...
In this paper we present a SLAM method based on indoor magnetic field anomalies and measure the acquired map quality in the context of the localization problem present in mobile robot floor-cleaning scenarios. According to our real-world robot experiments in different environments, it appears that most modern buildings have sufficient magnetic field variation to make the method applicable in mobile...
In this paper we examine near-optimal SLAM exploration in Gaussian processes. We propose a submodular sensing quality function that extends studies from discrete sensor placement to an autonomous sampling scheme where sensing sites must be visited frequently. This is beneficial in the SLAM context, where sensing sites themselves bear uncertainties. Also in time-critical applications, we have to balance...
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