Centre researchers – Niko Sünderhauf, Feras Dayoub, David Hall, John Skinner, Haoyang Zhang, Gustavo Carneiro and Peter Corke – reveal why a world-first robotic vision challenge has been developed to help robots sidestep the pitfalls of overconfidence in this ‘Challenge Accepted’ series published in Nature Machine Intelligence (September 2019).The Probabilistic Object Detection (PrOD) Challenge tasks competitors with detecting objects in cluttered settings, like lounge rooms, kitchens, bathrooms and outdoor living areas. Probabilistic object detection is important for robots to safely and effectively work in messy and unpredictable real-world environments.
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