Browsing by Author "Stroppa,F."

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Citation Count: 0
The Impact of Evolutionary Computation on Robotic Design: A Case Study with an Underactuated Hand Exoskeleton
(Institute of Electrical and Electronics Engineers Inc., 2024) Stroppa, Fabıo; Yuksel,H.T.; Soylemez,A.; Zyada,M.E.; Sarac,M.; Stroppa,F.
Robotic exoskeletons can enhance human strength and aid people with physical disabilities. However, designing them to ensure safety and optimal performance presents significant challenges. Developing exoskeletons should incorporate specific optimization algorithms to find the best design. This study investigates the potential of Evolutionary Computation (EC) methods in robotic design optimization, with an underactuated hand exoskeleton (U-HEx) used as a case study. We propose improving the performance and usability of the U-HEx design, which was initially optimized using a naive brute-force approach, by integrating EC techniques such as Genetic Algorithm and Big Bang-Big Crunch Algorithm. Comparative analysis revealed that EC methods consistently yield more precise and optimal solutions than brute force in a significantly shorter time. This allowed us to improve the optimization by increasing the number of variables in the design, which was impossible with naive methods. The results show significant improvements in terms of the torque magnitude the device transfers to the user, enhancing its efficiency. These findings underline the importance of performing proper optimization while designing exoskeletons, as well as providing a significant improvement to this specific robotic design. © 2024 IEEE.
Citation Count: 0
Optimizing Real-Time Decision-Making in Sensor Networks
(Institute of Electrical and Electronics Engineers Inc., 2023) Stroppa, Fabıo; Stroppa,F.; Badia,L.
The rapid integration of digital technologies into physical systems has given rise to cyber-physical systems, where the interaction between the computational and physical components plays a crucial role. This study explores optimal decision-making in event detection and transmission scheduling within cyber-physical systems, emphasizing the crucial aspect of efficient decision-making. We consider the problem of monitoring and reporting about a single event taking place within a finite time window achieving a reward related to the timeliness of the status update. Thus, the objective corresponds to minimizing the age of information between the instant of the event x and the status update time t, with a further penalty for a missed event. The monitoring apparatus decides when to perform the status update without knowing the value of x, but only knowing its statistical distribution. We assume a triangular probability density function for the instant of the event taking place, with a variable average. We provide an analytical derivation of the optimal choice of the status update, highlighting interesting trends, such as the saturation in the value of t as x grows close to the limit of the observation window. This proposed problem and its analytical formalization may serve as a further foundation for the general analysis of optimal monitoring of cyber-physical systems. © 2023 IEEE.