Abstract The paper models the unorganized chaining behavior, where humans need to walk in a chain due to a constrained environment. Detection and tracking are done using a 3D LiDAR,… Click to show full abstract
Abstract The paper models the unorganized chaining behavior, where humans need to walk in a chain due to a constrained environment. Detection and tracking are done using a 3D LiDAR, which has the challenges of environmental noises, uncontrolled environment, and occlusions. The Kalman filter is used for tracking. The trajectories are analyzed and used to train a behavioral model. The modeling has applications in socialistic robot motion planning and simulations. Based on the results, we conclude that the trajectory prediction by our approach is more socialistic and has a lesser error when compared to the artificial potential field method.
               
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