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Sanfilippo, F., & Rañó, I. (2023). Mimicking the Sense of Smell of Search and Rescue (SAR) Dogs: a Bio-inspired Steering Framework for Quadruped Robots. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 892–901). Omaha, USA: University of Nebraska at Omaha.
Abstract: Due to their sense of smell and ability to explore areas for missing people, dogs are valuable for search and rescue (SAR). Canines can discover humans under water, under snow, and even beneath crumbling structures because they can smell human scent. Building unmanned autonomous quadruped robots with canine agility is an attractive step to fully replicate the capabilities of dogs. Robots with legs are already capable of mimicking some of the physical traits of dogs, such as the capacity to traverse rough terrain. However, they would need to replicate also the level of sensory perception of a dog to successfully perform SAR operations. To achieve this, a navigation strategy that uses a direct sensor-motor coupling by following the principles of the Braitenberg vehicles is adopted in this work. This paper represents one of the first steps towards the connection of bio-inspired sensor-based steering mechanisms and bio-inspired locomotion for quadruped robots.
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Zeleskidis, A., Chalarampidou, S., Dokas, I. M., & Torra, F. (2023). COBOT Safety Awareness: A RealTSL Demonstration in a Simulated System. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 874–891). Omaha, USA: University of Nebraska at Omaha.
Abstract: This work aims to propose the RealTSL methodology to empower collaborative robotic systems with self-safety awareness capability and address the methodology's limitation in determining time ranges for the unsafe system state transitions, which are inputs of the methodology. The COBOT system used in this paper to demonstrate RealTSL is an automated scissor lift robot to be used by first responders for “work at height,” simulated in Simulink™. The demonstration begins by 1) applying STPA to the system, 2) applying Early Warning Sign Analysis based on STAMP (EWaSAP), 3) creating an acyclic diagram that depicts system state transitions towards unsafe states, 4) incorporating the appropriate sensory equipment in the simulation, 5) simulating the system's operation for different scenarios using fault injection and finally 6) use information from the simulations to complete the RealTSL analysis and calculate the safety level of the system in real-time during its simulated operation.
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