A bio-plausible design for visual pose stabilization

We consider the problem of purely visual pose stabilization (also known as servoing) of a second-order rigid-body system with six degrees of freedom: how to choose forces and torques, based on the current view and a memorized goal image, to steer the pose towards a desired one. Emphasis has been given to the bio-plausibility of the computation, in the sense that the control laws could be in principle implemented on the neural substrate of simple insects. We show that stabilizing laws can be realized by bilinear/quadratic operations on the visual input. This particular computational structure has several numerically favorable characteristics (sparse, local, and parallel), and thus permits an efficient engineering implementation. We show results of the control law tested on an indoor helicopter platform.

Authors

• Shuo Han 0011
• Andrea Censi
• Andrew D. Straw
• Richard M. Murray

Keywords

• Visualization
• Sensors
• Damping
• Asymptotic stability
• Approximation methods
• Pixel
• Dynamics
• Optimal Control
• Visual Input
• Neural Substrates
• Efficient Implementation
• Second-order System
• Control Input
• Rigid Body
• Postural Stability
• Fruit Fly
• Optical Flow
• Velocity Estimation
• Visual Control
• Contrast Variation
• Vision Sensors
• Translation Error
• Structure From Motion
• Compound Eyes
• Bilinear Form
• Decay Factor
• Proportional-derivative Control
• Visual Servoing
• Rotation Error
• Rigid Body Dynamics
• First-order System
• Gain Factor
• Structure Of Law
• Angular Velocity
• Region Of Attraction