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This paper addresses the problem of mitigating unknown partial path overlaps in communication systems. This study demonstrates that by utilizing the front-end insight of communication systems along with the sum–product algorithm applied to factor graphs, it is possible not only to track these overlapping components accurately, but also to detect all multipath channel impairments simultaneously. The proposed methodology involves discretizing channel parameters, such as channel paths and attenuation coefficients, to ensure the most accurate computation of means of Gaussian observations. These parameters are modeled as Bernoulli random variables with priors set to 0.5. A notable aspect of the algorithm is its integration of the received signal power into the calculation of noise variance, which is critical for its performance. To further reduce the receiver complexity, a novel implementation strategy, based on provided pre-defined look up tables (LOTs) to the reciver, is introduced. The simulation results, covering both distributed and concentrated pilot scenarios, reveal that the algorithm performs almost equally under both conditions and surpasses the established upper bound in performance.

This paper addresses the problem of mitigating unknown partial path overlaps in communication systems. This study demonstrates that by utilizing the front-end insight of communication systems along with the sum–product algorithm applied to factor graphs, it is possible not only to track these overlapping components accurately, but also to detect all multipath channel impairments simultaneously. The proposed methodology involves discretizing channel parameters, such as channel paths and attenuation coefficients, to ensure the most accurate computation of means of Gaussian observations. These parameters are modeled as Bernoulli random variables with priors set to 0.5 . A notable aspect of the algorithm is its integration of the received signal power into the calculation of noise variance, which is critical for its performance. To further reduce the receiver complexity, a novel implementation strategy, based on provided pre-defined look up tables (LOTs) to the reciver, is introduced. The simulation results, covering both distributed and concentrated pilot scenarios, reveal that the algorithm performs almost equally under both conditions and surpasses the established upper bound in performance. [ABSTRACT FROM AUTHOR]

In this work, we tested a recently developed novel methodology to assist children with Autism Spectrum Disorder (ASD) improve their Visual Perspective Taking (VPT) and Theory of Mind (ToM) skills using the humanoid robot Kaspar. VPT is the ability to see the world from another person’s perspective, drawing upon both social and spatial information. Children with ASD often find it difficult to understand that others might have perspectives, viewpoints and beliefs that are different from their own, which is a fundamental aspect of both VPT and ToM. The games we designed were implemented as the first attempt to study if these skills can be improved in children with ASD through interacting with a humanoid robot in a series of trials. The games involved a number of different actions with the common goal of helping the children to see the world from the robot’s perspective. Children with ASD were recruited to the study according to specific inclusion criteria that were determined in a previous pilot study. In order to measure the potential impact of the games on the children, three pre- and post-tests (Smarties, Sally–Anne and Charlie tests) were conducted with the children. Our findings suggest that children with ASD can indeed benefit from this approach of robot-assisted therapy.

Visual Perspective Taking (VPT) is the ability to see the world from another person’s perspective, taking into account what they see and how they see it, drawing upon both spatial and social information. Children with autism often find it difficult to understand that other people might have perspectives, viewpoints, beliefs and knowledge that are different from their own, which is a fundamental aspect of VPT. In this research we aimed to develop a methodology to assist children with autism develop their VPT skills using a humanoid robot and present results from our first long-term pilot study. The games we devised were implemented with the Kaspar robot and, to our knowledge, this is the first attempt to improve the VPT skills of children with autism through playing and interacting with a humanoid robot.We describe in detail the standard pre- and post-assessments that we performed with the children in order to measure their progress and also the inclusion criteria derived fromthe results for future studies in this field. Our findings suggest that some children may benefit from this approach of learning about VPT, which shows that this approach merits further investigation.

The problem of velocity tracking is considered essential in the consensus of multi-wheeled mobile robot systems to minimise the total operating time and enhance the system’s energy efficiency. This study presents a novel switched-system approach, consisting of bang-bang control and consensus formation algorithms, to address the problem of time-optimal velocity tracking of multiple wheeled mobile robots with nonholonomic constraints. This effort aims to achieve the desired velocity formation in the least time for any initial velocity conditions in a multiple mobile robot system. The main findings of this study are as follows: (i) by deriving the equation of motion along the specified path, the motor’s extremal conditions for a time-optimal trajectory are introduced; (ii) utilising a general consensus formation algorithm, the desired velocity formation is achieved; (iii) applying the Pontryagin Maximum Principle, the new switching formation matrix of weights is obtained. Using this new switching matrix of weights guarantees that at least one of the system’s motors, of either the followers or the leader, reaches its maximum or minimum value by using extremals, which enables the multi-robot system to reach the velocity formation in the least time. The proposed approach is verified in a theoretical analysis along with the numerical simulation process. The simulation results demonstrated that using the proposed switched system, the time-optimal consensus algorithm behaved very well in the networks with different numbers of robots and different topology conditions. The required time for the consensus formation is dramatically reduced, which is very promising. The findings of this work could be extended to and beneficial for any multi-wheeled mobile robot system.