17 Computer Vision News AIRLab Politecnico di Milano The Robotic Drone Contest is a competition supported by Leonardo, an Italian aerospace, defense, and security company. Initially involving six universities in Italy, it has recently expanded its reach to include institutions from other countries. Simone tells us that for the first three years, the contest focused on participants building aerial drones and developing algorithms for navigation in new environments. Last year, this focus expanded to multi-agent cooperation. “In this scenario, we still have drones, but we also have a ground robot,” he says. “The goal is to develop algorithms that allow cooperation between these agents to explore a partially unknown environment and identify and track targets of interest.” Winning the contest requires a strategic approach. Participants go through multiple rounds, aiming to locate specific targets within the environment accurately and efficiently. Success is measured by the time taken to find targets and the precision of their positioning on a map, leading to a decisive formula for determining the winner. However, securing the victory comes at the end of a challenging process. Simone highlights the delicate balance between computational power and flight time in design considerations. “For our task, we required a lot of computational power because we had to identify targets and obstacles fully autonomously,” he explains. “We had a trade-off between how long the drone could fly and the payload computationally on board. We added more computational power, boards, and sensors, so the drone’s flight time constantly reduced with increased power on board.” All the computation is performed onboard the drone, with only limited information provided to the ground control stations. Simone points out that part of the computation could have been offloaded to agents, but not doing this helped to optimize performance in a scenario where bandwidth was limited and the Wi-Fi connection was unstable. Reflecting on their winning strategy, Simone credits the team’s success to a robust and efficient solution rather than advanced algorithms. “We wrote most of the communication on layers and most
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