Trajectory time scaling of a mobile robot to avoid dynamic obstacles on the basis of the INLVO

Chang Bae Moon, Woojin Chung

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


To ensure the collision safety of mobile robots, the velocity of dynamic obstacles should be considered while planning the robot's trajectory for high-speed navigation tasks. A planning scheme that computes the collision avoidance trajectory by assuming static obstacles may result in obstacle collisions owing to the relative velocities of dynamic obstacles. This article proposes a trajectory time-scaling scheme that considers the velocities of dynamic obstacles. The proposed inverse nonlinear velocity obstacle (INLVO) is used to compute the nonlinear velocity obstacle based on the known trajectory of the mobile robot. The INLVO can be used to obtain the boundary conditions required to avoid a dynamic obstacle. The simulation results showed that the proposed scheme can deal with typical collision states within a short period of time. The proposed scheme is advantageous because it can be applied to conventional trajectory planning schemes without high computational costs. In addition, the proposed scheme for avoiding dynamic obstacles can be used without an accurate prediction of the obstacle trajectories owing to the fast generation of the time-scaling trajectory.

Original languageEnglish
Pages (from-to)1189-1198
Number of pages10
JournalAdvanced Robotics
Issue number15
Publication statusPublished - 2013 Jul

Bibliographical note

Funding Information:
This work was supported by the NRF grant funded by the MEST, Korea (2013-029812). This research was also supported in part by the MKE, Korea, under the Human Resources Development Program supervised by the NIPA (NIPA-2013-H1502-13-1001). This research was also supported by the MKE, Korea, under the ITRC support program (NIPA-2013-H0301-13-2006). The research was also supported in part by the Implementation of Technologies for Identification, Behavior, and Location of Human based on Sensor Network Fusion Program through the MKE (Grant Number: 10041629). This work also was supported by a Korea University Grant. This work was also supported by Korea University during the sabbatical year of the second author.


  • Mobile robot
  • Mobstacle avoidance
  • Nonlinear velocity obstacles
  • Trajectory time scaling

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Human-Computer Interaction
  • Hardware and Architecture
  • Computer Science Applications


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