Future trajectory predictions in multi-actor environments for autonomous machine
A Kamenev, N Smolyanskiy, I Kulkarni… - US Patent …, 2024 - Google Patents
In various examples, past location information corresponding to actors in an environment
and map information may be applied to a deep neural network (DNN)—such as a recurrent
neural network (RNN)—trained to compute information corresponding to future trajectories
of the actors. The output of the DNN may include, for each future time slice the DNN is
trained to predict, a confidence map representing a confidence for each pixel that an actor is
present and a vector field representing locations of actors in confidence maps for prior time …
and map information may be applied to a deep neural network (DNN)—such as a recurrent
neural network (RNN)—trained to compute information corresponding to future trajectories
of the actors. The output of the DNN may include, for each future time slice the DNN is
trained to predict, a confidence map representing a confidence for each pixel that an actor is
present and a vector field representing locations of actors in confidence maps for prior time …
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