Abstract
The future of robotics is now trending for home servicing. Nursing homes and assistance to elder peopleare areas where robots can provide valuable help in order to improve the quality of life of those who need it most. Calling a robot,for a person of age,can be a daunting task if the voice is failing and any resort to battery operated devices failsto comply. Using a simple mechanical apparatus,such as aClick trainerfordogs, a person can call a robot by pressing thebutton of a powerless device. The high pitch sound produced by this device can be captured and tracked down in order to estimate the person’s location within a room. This paper describes a method that provides good accuracy and uses simple and low cost technology,in order to provide an efficient positional value for an assistance robot to attend its caller. The robot does not need to search for the person in aroom as it can directly travel towards the Click’s sound source.

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Abstract
Solving complex optimization problems with genetic algorithms (GAs) with custom computing architectures is a way to improve the execution time of this metaheuristic, which is known to consume considerable amounts of time to converge to final solutions. In this work, we present a scalable computing array architecture to accelerate the execution of cellular GAs (cGAs), a variant of genetic algorithms which can conveniently exploit the coarse- grain parallelism afforded by custom parallel processing. The proposed architecture targets Xilinx FPGAs and is used as an auxiliary processor of an embedded CPU (MicroBlaze). To handle different optimization problems, a high- level synthesis (HLS) design flow is proposed where the problem- dependent operations are specified in C++ and synthesised to custom hardware, thus requiring a minimum knowledge of digital design for FPGAs. The minimum energy broadcast (MEB) problem in wireless ad hoc networks is used as a case study. An existing software implementation of a GA to solve this problem is ported to the proposed computing array to demonstrate its effectiveness and the HLS- based design flow. Implementation results in a Virtex- 6 FPGA show significant speedups, while finding solutions with improved quality.

Abstract
Today there are different teams specializing in different areas such as shipwrecked rescue, searching for mines, environmental monitoring, border surveillance, traffic control, search and rescue and harbor protecting. Robotic systems and unmanned vehicles can provide additional capabilities and new innovative solutions that contribute to these applications. This paper presents the Robotic Exercises 2014 (REX'14) and the lessons learned with various field experiments performed with multiple unnamed systems in the context of the Portuguese Navy concept of operations. During the REX'2014 multiple experiments and systems were operated. Autonomy and environment characterization and assessment missions were performed with autonomous surface vehicles such as the ROAZ autonomous surface vehicle or with autonomous underwater vehicle MARES. Autonomy and system validation was performed for fast water jet propelled surface systems such as the SWIFT autonomous surface vehicle and the ICARUS unmanned rescue capsule, wind propulsion tests were also performed with unnamed surface vehicles and new maritime wireless communication protocols were tested.

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Abstract