In this paper, we describe a new jumping behaviour developed for the quadruped robot, PAW (Platform for Ambulating Wheels). The robot has very few degrees of freedom and no knee joints. It employs springy legs and wheels at the distal ends of the legs to achieve various modes of legged, wheeled, and hybrid locomotion, such as high-speed breaking, bounding, and presently jumping. The jumping maneuver developed in this manuscript is designed specifically to take advantage of the wheels on the robot and compliance in its legs and it involves the following principal stages: acceleration to jumping speed, body positioning via front hip thrusting, rear leg compression and thrusting, and flight. A high-fidelity MSC.ADAMS/Simulink co-simulation was developed and used to test and optimize the jumping process. Because of the strong coupling between the parameters defining the jump maneuver, manual parameter tuning is difficult and thus a genetic algorithm is employed for the optimization process. The data generated by the genetic algorithm is further used for the fitting of a quadratic response surface, which allows identifying those parameters that contribute most to a successful jump. Finally, the jumping maneuver is implemented on the physical PAW to demonstrate its feasibility on a hybrid quadruped, and to provide insights into the robot response during this highly dynamic maneuver.
Genetic algorithm hyper-parameter optimization using Taguchi design for groundwater pollution source identification
