![]() To give some valuable examples, in Taborri et al., 2020, the authors present B.E.A.T., a benchmark for evaluating the static and dynamic balance of wearable human-assisting devices. Seventeen sub-projects work under the Eurobench consortium, each accounting for a different aspect of robot performance. Torricelli et al., 2015 and Torricelli and Pons, 2018 paved the way for benchmarking platforms for self-stabilizing robots and exoskeletons with the European Project EUROBENCH 2020 1. Hence, a growing interest in the field of benchmarking has arisen during recent years in the research community ( Negrello et al. (2020)) ( Stasse et al. (2018)), especially for legged systems ( Torricelli et al., 2015). In industry, performance quantification makes possible standardization of technologies and regulation of the processes for manufacturing and commercialization of certified robots ( Torricelli et al., 2015). It allows for quantifying the performance of various systems, making comparisons possible, and fostering improvements. ![]() Benchmarking the performance of robotic systems offers many advantages. These assessment methods are qualitative or hardly repeatable and do not allow comparisons between different robots. Nevertheless, in the related literature, it is possible to find just heuristic tests: Pushes) ( Barasuol et al., 2013) ( Feng et al., 2016), tilting the support surface ( Li et al., 2013), balancing over a soft ground ( Henze et al., 2016), or impacting with heavy masses ( Kanzaki et al., 2005). To this aim, one of the most advanced fields is the legged locomotion research community. However, nowadays, the measurement of robots’ balancing resilience is a novel research field and still mostly relies on qualitative methods. In this sense, studying the resilience of robots becomes closely connected to looking into balancing abilities. As a result, for these robots, the concept of resilience expressed by Zhang and Lin, 2010 should be re-defined as the ability of a system to maintain a stable state, allowing it to continue operating in the presence of continuous and significant perturbations. In the face of this augmented dexterity, the possibility of facing unexpected falls, which may cause damage to the robot, the surroundings, or persons, arises and become the major issue for a self-stabilizing robot to cease operations. Their increment of control and design complexity is accepted in the face of the augmented dexterity and agility that they show when compared to stable robots, such as mobile base robots ( Fuchs et al., 2009). Self-stabilizing robots are a group of robotic systems with the common trait of possessing an unstable equilibrium stabilized continuously through control. Zhang brought the concept of resilience into the robotic field ( Zhang and Lin, 2010), while Zhang et al., 2017 proposes a set of principles for the design of soft and resilient robots.įollowing Hollnagel and Zhang’s interpretations, we investigate the definition of resilience for self-stabilizing robots. In engineering, Hollnagel et al. (2006) defined resilience as “the ability of an organization (system) to keep or recover quickly to a stable state, allowing it to continue operations during and after a major mishap or in the presence of continuous significant stresses”. The growing employment of robots in real-world applications, e.g., exploration of hazardous environments ( Negrello et al., 2018) and household assistance ( Parmiggiani et al., 2017), emphasizes the necessity of robots safe and resilient against disturbances. The investigation demonstrates high repeatability and efficacy in executing reliable and precise perturbations. As an example of the application of our method, we report a set of experimental tests on a two-wheeled humanoid robot, with an experimental campaign of more than 1100 tests. The design of the testbed, the control structure, the post-processing software, and all the documentation related to the performance indicators and protocols are provided as open-source material so that other institutions can replicate the system. Our proposed framework consists of a set of novel Performance Indicators (PIs), experimental protocols for the reliable and repeatable measurement of the PIs, and a novel testbed to execute the protocols. This work presents a framework that quantitatively assesses the balancing resilience of self-stabilizing robots subjected to external perturbations. Accordingly, recently, researchers focused on designing robust and resilient systems. Robots that work in unstructured scenarios are often subjected to collisions with the environment or external agents. ![]() 2Istituto Italiano di Tecnologia, Genova, Italy.Piaggio e Dipartimento di Ingegneria dell’Informazione, Università di Pisa, Pisa, Italy ![]() Catalano 2 Antonio Bicchi 1,2 Manolo Garabini 1 Simone Monteleone 1* Francesca Negrello 2 Giorgio Grioli 2 Manuel G. ![]()
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