Orthoses, or exoskeletons as they’re more commonly known, are a method to either assist those with reduced mobility in certain parts of their body, or to completely reintroduce function… Read more
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The market of domestic service robots, and especially vacuum cleaners, has kept growing during the past decade. According to the International Federation of Robotics, more than 1 million units were sold worldwide in 2010. Currently, there is no in-depth analysis of the energetic impact of the introduction of this technology on the mass market. This topic is of prime importance in our energy-dependant society. This study aims at identifying key technologies leading to the reduction of the energy consumption of a domestic mobile robot, by exploring the design space using technologies issued from the robotic research field, such as the various localization and navigation strategies. This approach is validated through an in-depth analysis of seven vacuum cleaning robots. These results are used to build a global assessment of the influential parameters. The major outcome is the assessment of the positive impact of both the ceiling-based visual localization and the laser-based localization approaches.
This paper proposed a fuzzy controller for the autonomous navigation problem of robotic systems in a dynamic and uncertain environment. In particular, we are interested in determining the robot motion to reach the target while ensuring their own safety and that of different agents that surround it. To achieve these goals, we have adopted a fuzzy controller for navigation and avoidance obstacle, taking into account the changing nature of the environment. The approach has been tested and validated on a Thymio II robots set. As application field, we have chosen a parking problem.
We report on real-robot odor source localization experiments carried out in an environment with obstacles in the odor plume. The robot was equipped with an ethanol sensor and a wind direction sensor, and the experiments were carried out in a wind tunnel, i.e. in a controlled environment. An enhanced version of the surge-spiral algorithm was used, which was augmented with a dedicate behavior to manage obstacles (avoid them, or follow their contour). We compare the results in terms of distance overhead and success rate, and discuss the impact of obstacles on plume traversal.
Domestic service robots are currently powered by the mains electricity. The growing multiplication of such devices negatively impacts our environment. In this study, we show the feasibility of harvesting energy from natural light in an indoor environment. The design of the harvester is carefully carried out using an experimental characterisation of several solar panels, while the boost converter is optimised to operate at low-light intensities and the robot is enhanced for low-power operations. The resulting harvester is then thoroughly characterised. Finally, a phototaxis experiment is conducted, proving the feasibility of recharging the robot solely by using this form of energy. The possibility of embedding energy harvesting in indoor mobile robots radically changes the potential impact of this technology in our society.
It is often challenging to manage the battery supply when dealing with a fleet of mobile robots during long experiments. If one uses classical recharge stations, then agents are immobilized during the whole recharge process. In this study, we present a novel approach that employs a battery pack swapping station. Batteries are charged in a rotating barrel, and the robots dock only for the time of the hot-swap process. We attained an unavailability time of only 40 seconds, with a success rate of 100 % on a total of 46 trials. Experiments above 8 hours are performed in three arenas with different configurations, which proves the relevance of our approach.