A Novel Trajectory Generator Based on a Constrained GAN and a Latent Variables Predictor

• Published in: IEEE access Vol. 8; pp. 212529 - 212540
• Main Authors: Wu, Wei, Yang, Biao, Wang, Dong, Zhang, Weigong
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Constraints; future uncertainty; generative adversarial network; Generative adversarial networks; Generators; Hidden Markov models; latent variable predictor; Optimization; Pedestrians; Predictive models; Random noise; Random variables; Robots; Social factors; Training; Trajectory; Trajectory forecasting; Uncertainty

Forecasting pedestrian trajectory is critical for versatile applications, such as autonomous driving and social robot, when they work in human-centric environments. However, it is challenging to predict pedestrians' future trajectories due to the inherent human properties and pedestrians'...