Role playing learning for socially concomitant mobile robot navigation

Role playing learning for socially concomitant mobile robot navigation

In this study, the authors present the role playing learning scheme for a mobile robot to navigate socially with its human companion in populated environments. Neural networks (NNs) are constructed to parameterise a stochastic policy that directly maps sensory data collected by the robot to its velo...

Full description

Bibliographic Details
Main Authors: Mingming Li, Rui Jiang, Shuzhi Sam Ge, Tong Heng Lee
Format: Article
Language:English
Published: Wiley 2018-04-01
Series:CAAI Transactions on Intelligence Technology
Subjects:
mobile robots
learning (artificial intelligence)
path planning
human-robot interaction
learning iteration
NN policy
companied pedestrian
role playing learning
reinforcement learning framework
socially concomitant mobile robot navigation
learning scheme
stochastic policy
social norms
pedestrians trajectories
sensory data
trust region policy optimisation
simulative learning environment
robot sensor measurements
Online Access:https://digital-library.theiet.org/content/journals/10.1049/trit.2018.0008

Internet

https://digital-library.theiet.org/content/journals/10.1049/trit.2018.0008

Similar Items