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Browsing Research by Department "Computer Science and AI"
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Publication DJESTHESIA: Tangible Multimedia for DJs(ACM, 2025-07-15) Eduardo Castelló Ferrer; https://ror.org/02jjdwm75DJESTHESIA uses tangible interaction to craft real-time audiovisual multimedia, blending sound, visuals, and gestures into a unified live performance. The project supports four interaction modes: I) Knob changes music, where standard DJing is performed. II) Music changes visuals, where changes in the audio parameters done through the mixer have a direct impact in the visualizations representing the music (e.g., color palette). III) Gesture changes visuals, where gestures and body movements give the possibility to interact physically with the visual representation of the music (e.g., grab, release, throw). IV) Gesture changes music, where, gestures can convey information to an audio composition software to alter aspects of the music being played (e.g., EQs). The aim of DJESTHESIA is to transform the DJ into both a performer and a performance.Publication Secure and secret cooperation in robotic swarms(Science, 2021-07-21) Castelló, Eduardo; Hardjono, Thomas; Pentland, Alex 'Sandy'; Dorigo, Marco; https://ror.org/02jjdwm75The importance of swarm robotics systems in both academic research and real-world applications is steadily increasing. However, to reach widespread adoption, new models that ensure the secure cooperation of large groups of robots need to be developed. This work introduces a method to encapsulate cooperative robotic missions in an authenticated data structure known as a Merkle tree. With this method, operators can provide the “blueprint” of the swarm’s mission without disclosing its raw data. In other words, data verification can be separated from data itself. We propose a system where robots in a swarm, to cooperate toward mission completion, have to “prove” their integrity to their peers by exchanging cryptographic proofs. We show the implications of this approach for two different swarm robotics missions: foraging and maze formation. In both missions, swarm robots were able to cooperate and carry out sequential tasks without having explicit knowledge about the mission’s high-level objectives. The results presented in this work demonstrate the feasibility of using Merkle trees as a cooperation mechanism for swarm robotics systems in both simulation and real-robot experiments, which has implications for future decentralized robotics applications where security plays a crucial role.