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Widening applications of inertial sensors has triggered the search for cost effective sensors and those based on MEMS technology has been gaining popularity in particular for the lower cost applications. However, inertial sensors are subject to various error sources and characteristics of these should be modelled carefully and corrective calibration(More)
In this paper, we study the kinematics of a legged robot with half-circular leg morphology. In particular, our focus is on the RHex hexapod platform. A new kinematic model for RHex is developed considering the leg shape and its consequences, which was over simplified in the previous models seen in literature. The formulation is an accurate kinematic(More)
Pronking (aka. stotting) is a gait in which all legs are used in synchrony, resulting in long flight phases and large jumping heights that may potentially be useful for mobile robots on rough terrain. Robotic instantiations of this gait suffer from severe pitch instability either due to underactuation, or the lack of sufficient feedback. Nevertheless, the(More)
This study presents a theoretical analysis of output independence and complementariness between classiiers in a rank-based multiple classiier decision system in the context of the Partitioned Observation Space theory. T o enable such an analysis, an Information Theoretic interpretation of a rank-based multiple classiier system is developed and basic(More)
A promising line of research attempts to bridge the gap between radar detector and radar tracker by means of considering jointly optimal parameter settings for both of these subsystems. This approach, which can also be considered as a form of feedback from the tracker to the detector results in an adaptive radar system. In the present work, we attempt to(More)
This study presents a theoretical investigation of the rank-based multiple classifier decision problem for closed-set pattern identification. The problem of combining the decisions of more than one classifiers with raw outputs in the form of candidate class rankings is considered and formulated as a general discrete optimization problem with an objective(More)
In this study, the problem of real-time chaotic time-series prediction using Radial Basis Function Networks is addressed. The performance of a number of training methods based either on supervised error correction or on adaptive clustering techniques are investigated. Some performance drawbacks due to their exclusive usage are pointed out and a new(More)