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A unified strategy for landing and docking using spherical flow divergence.

Chris McCarthy1, Nick Barnes

  • 1NICTA Canberra Research Laboratory and College of Engineering and Computer Science, Australian National University, Tower A, 7 London Circuit, Canberra, ACT 2601, Australia. chris.mccarthy@nicta.com.au

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Summary

This study introduces maximum flow field divergence (max-div) as a novel visual cue for robot docking and landing. This method enables unified control laws for approaching surfaces of any orientation without needing egomotion data.

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Area of Science:

  • Robotics
  • Computer Vision
  • Control Systems

Background:

  • Existing visual control methods for docking and landing often require knowledge of surface orientation or egomotion.
  • A directly observable visual cue for approaching arbitrary surfaces under general motion is lacking.

Purpose of the Study:

  • To introduce a novel visual control input based on optical flow divergence for unified control laws in docking and landing.
  • To develop control strategies that do not require structure-from-motion recovery or knowledge of surface orientation and egomotion.

Main Methods:

  • Utilizing the maximum flow field divergence on the view sphere (max-div) as the primary visual cue.
  • Proving kinematic properties of max-div to establish its temporal proximity measure.
  • Developing novel control laws for regulating approach velocity and angle.

Main Results:

  • Demonstrated that max-div provides a reliable temporal measure of proximity to surfaces.
  • Successfully regulated approach velocity and angle towards planar surfaces of arbitrary orientation.
  • Validated the strategy through simulations, real image sequences, and closed-loop control experiments.

Conclusions:

  • Maximum flow field divergence (max-div) offers a powerful, directly observable visual cue for robotic docking and landing.
  • The proposed control laws enable robust and unified approach maneuvers without relying on egomotion or surface orientation estimation.