Interactive Natural Motion Planning for Robot Systems Based on Representation Space

  • Guofei Xiang
  • Jianbo SuEmail author


Endowing robot with interactive natural motion planning is of great importance, since user has to get more and more involved for better realization with versatile tasks under increasingly complicated environments. In this paper, studies on interactive natural motion planning are summarized and a general theoretic framework for which is presented in triple-folds. Firstly, the motion planning model is formulated based on representation space, and essential guidelines on planning algorithm selection are also proposed. Then user intention inference, which consists of grid-based intention model and Bayesian filtering based inferring algorithm, is investigated to mitigate the impact of network induced imperfections during human–robot interaction. Finally, for further rejecting various uncertainties, \({\mathcal {H}}_\infty \) control theory based disturbance observer is proposed. All three algorithmic design procedures are stated in detail and the efficiency of which are presented via existing results, followed by discussions on the future directions.


Robot Interactive natural motion planning Representation space Intention inference Bayesian filtering Disturbance observer 



This work was supported by National Natural Science Foundation of China (NFSC) under Grants 61533012, 91748120 and 61521063.

Compliance with Ethical Standards

Conflict of interest

The authors declare that they have no conflict of interest.


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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Department of AutomationShanghai Jiao Tong UniversityShanghaiPeople’s Republic of China

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