Dynamic Grasping in Space using Adhesive Grippers and Model Predictive Control

Spacecraft equipped with gecko-inspired dry adhesive grippers can dynamically perch on and grasp a wide variety of featureless surfaces. In this paper we explore the use of model predictive control (MPC) for autonomous docking onto and acquisition of free-floating, spinning objects. First, we extend previous work characterizing the dynamic grasping capabilities of these grippers to the case where both object and spacecraft are free-floating and comparably sized. We then formulate the acquisition problem as an MPC problem, whereby the terminal constraints for grasping are cast as linear constraints and the problem is solved as a Quadratic Program (thus amenable to real-time implementation on space-qualified hardware). We provide formal performance guarantees in terms of persistent feasibility and closed-loop stability, and present numerical experiments corroborating our theoretical findings.