Optimization-based design of a novel hybrid aerial/ground mobile manipulator

This paper is concerned with the mechanical design of a mobile manipulating unmanned ground vehicle (MM-UGV) coupled with an existing commercial unmanned aerial vehicle (UAV) to create a novel hybrid aerial/ground mobile manipulator. A novel systematic optimization-based approach is presented for making important design choices, such as the selection of gearboxes and electric DC motors in the drive-train, manipulator link lengths, and UGV base length. The objective is to minimize the overall mass of the MM-UGV. Constraints related to workspace, dynamic tip-over stability, actuator torque/force limits in static and dynamic motions, executed in the air or on the ground, and battery properties are incorporated into the problem formulation. The system operating conditions in the form of the range of end-effector forces, operating surface grade, and various position, velocity and acceleration variables are provided by the designer. The resulting problem is a robust bilevel nonlinear optimization, in which some of the constraints are derived from maximization/minimization over the operational variables to ensure constraint satisfaction in all possible operation scenarios. The problem is solved using a genetic algorithm. Numerical simulations demonstrate that the proposed strategy produces a design that meets the user-specified requirements.