Adaptation of Gradient-Based Navigation Control for Holonomic Robots to Nonholonomic Robots

Amir Salimi Lafmejani, Hamed Farivarnejad, Spring Berman

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


In this letter, we propose a gradient-based nonlinear control approach for stabilizing a nonholonomic Wheeled Mobile Robot (WMR) to a target position in environments with and without obstacles. This approach enables any gradient-based feedback control law (with bounded or unbounded gradients) developed for a holonomic point-mass robot model to be adapted to control a nonholonomic robot. The proposed controller is defined in terms of smooth continuous functions, which produce smooth robot trajectories and can be tuned to stabilize the robot to the goal position at a desired convergence rate. We first prove that the controller will stabilize a nonholonomic robot to a target point in an obstacle-free environment. To stabilize the robot's position in environments with obstacles, we modify our controller to utilize the gradient of an artificial potential function and use Lyapunov stability theory to prove that the robot is guaranteed to converge to the target position under this controller. We demonstrate the effectiveness of our controller for various initial robot positions and environments, and two types of potential fields that are widely used in gradient-based methods for obstacle avoidance, through MATLAB simulations and experiments with a commercial nonholonomic WMR.

Original languageEnglish (US)
Article number9258372
Pages (from-to)191-198
Number of pages8
JournalIEEE Robotics and Automation Letters
Issue number1
StatePublished - Jan 2021


  • Artificial potential field
  • nonholonomic constraint
  • nonlinear controller
  • obstacle avoidance
  • wheeled mobile robots

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Biomedical Engineering
  • Human-Computer Interaction
  • Mechanical Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Control and Optimization
  • Artificial Intelligence


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