T oday, human intervention is the only effective course of action after a natural or artificial disaster. This is true both for relief operations, where search and rescue of survivors is the priority, and for subsequent activities, such as those devoted to building assessment. In these contexts, the use of robotic systems would be beneficial to drasti cally reduce operators' risk exposure. However, the readiness level of robots still prevents their effective exploitation in relief operations, which are highly critical and characterized by severe time constraints. On the contrary, current robotic technologies can be profitably applied in procedures like building assessment after an earthquake. To date, these operations are carried out by engineers and architects who inspect numerous buildings over a large territory, with a high cost in terms of time and resources, and with a high risk due to aftershocks. The main idea is to have the robot acting as an alter ego of the human operator, who, thanks to a virtual-reality device and a body-tracking system based on inertial sensors, teleoperates the robot. The goal of this article is to discuss the exploitation of the perception and manipulation capabilities of the WALK-MAN robot for building assessment in areas affected by earthquakes. The presented work illustrates the hardware and software characteristics of the developed robotic platform and results obtained with field testing in the real earthquake scenario of Amatrice, Italy. Considerations on the experience and feedback provided by civil engineers and architects engaged in the activities are reported and discussed.
Autonomous vehicles are undergoing a rapid development thanks to advances in perception, planning and control methods and technologies achieved in the last two decades. Moreover, the lowering costs of sensors and computing platforms are attracting industrial entities, empowering the integration and development of innovative solutions for civilian use. Still, the development of autonomous racing cars has been confined mainly to laboratory studies and small to middle scale vehicles. This paper tackles the development of a planning and control framework for an electric full scale autonomous racing car, which is an absolute novelty in the literature, upon which we report our preliminary experiments and perspectives on future work. Our system leverages real time Nonlinear Model Predictive Control to track a pre-planned racing line. We describe the whole control system architecture including the mapping and localization methods employed.
H istorically, robots first found application in factories and plants. Until recently, the most noticeable examples of robot systems direct ly sold to the consumer were limited to edutain ment systems (e.g., NAO [1]), automated chore robots [26], and social telepresence platforms [27]. Initially, telepresence robots consisted of a mobile base with an interactive screen. Today, following a trend of anthropomorphization of technology, humanlike upper bodies have begun to replace those simple screens (e.g., Pepper [2] and R1 [3]) and share the same social communication modalities of humans, e.g., body posture, gestures, gaze direction, and facial expressions. Un fortunately, social robots are mostly designed to speak and make gestures and have limited capabilities when it comes to physically interacting with people and their surround ing environments. On the other hand, looking at the state of art, there are promising examples (e.g., WALKMAN [4], Atlas [5], and TORO [6]) of humanoid robots that have been developed to operate in unstructured environments and perform challenging interaction tasks, e.g., walking on rough ter rains, moving heavy objects, and solving complex biman ual manipulation tasks. Specific enabling technologies have improved the effectiveness of these robots and facili tate their interactions with the surrounding world, e.g., active impedance control in TORO and serieselastic actuation in WALKMAN. Indeed, these same technolo gies permit robot arms to cross the borders of industrial work cells and become the type of collaborative robots that can work in close contact with people and share the same operating space. Although both humanoid robotics and teleoperation have a long history, we believe that three concurrent factors ALTER-EGO
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