Coordinated Heterogeneous Distributed Perception based on Latent Space Representation

We investigate a reinforcement approach for distributed sensing based on the latent space derived from multi-modal deep generative models. Our contribution provides insights to the following benefits: Detections can be exchanged effectively between robots equipped with uni-modal sensors due to a shared latent representation of information that is trained by a Variational Auto Encoder (VAE)... (read more)

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