In this article, the ultra-wideband technology for localization and tracking of the robot gripper (behind the obstacles) in industrial environments is presented. We explore the possibilities of ultra-wideband radar sensor network employing the centralized data fusion method that can significantly improve tracking capabilities in a complex environment. In this article, we present ultra-wideband radar sensor network hardware demonstrator that uses a new wireless ultra-wideband sensor with an embedded controller to detect and track online or off-line movement of the robot gripper. This sensor uses M-sequence ultra-wideband radars front-end and low-cost powerful processors on a system on chip with the advanced RISC machines (ARM) architecture as a main signal processing block. The ARM-based single board computer ODROID-XU4 platform used in our ultra-wideband sensor can provide processing power for the preprocessing of received raw radar signals, algorithms for detection and estimation of target’s coordinates, and finally, compression of data sent to the data fusion center. Data streams of compressed target coordinates are sent from each sensor node to the data fusion center in the central node using standard the wireless local area network (WLAN) interface that is the feature of the ODROID-XU4 platform. The article contains experimental results from measurements where sensors and antennas are located behind the wall or opaque material. Experimental testing confirmed capability of real-time performance of developed ultra-wideband radar sensor network hardware and acceptable precision of software. The introduced modular architecture of ultra-wideband radar sensor network can be used for fast development and testing of new real-time localization and tracking applications in industrial environments.

SUMMARYGiven the advanced breakthroughs in the field of supportive robotic technologies, interest in the integration of the human body and a robot into a single system has rapidly increased. The aim of this work is to provide an overview of empowering lower limbs exoskeletons. Along with lower exoskeleton limbs, their unique design concepts, operator–exoskeleton interactions and control strategies are described. Although many problems have been solved in recent development, many challenges remain. Especially in the context of infantry soldiers, fire fighters and rescuers, the challenges of empowering exoskeletons are discussed, and improvements are outlined and described. This study is not only a summary of the current state, but also points to weaknesses of empowering lower limbs exoskeletons and outlines possible improvements.

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Different biometric methods are available for identification purpose of a person. The most commonly used are fingerprints, but there are also other biometric methods such as voice, morphology of ears, structure of iris and so on. In some cases, it is required to identify a person according to his/her biomechanical parameters or even his/her gait pattern. Gait is an outstanding biometric behavioural characteristic that is not widely used yet for identification purposes because efficient and proven automated processes are not yet available. Several systems and gait pattern databases have been developed for rapid evaluation and processing of gait. This article describes an original automated evaluation procedure of gait pattern and identification of unique gait parameters for automatic identification purposes.

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