Skill learning based catching motion control
Learned biomechanical strategies prepare the human body in kinematics and kinetics terms during interception tasks, such as throwing and catching, in real world. Based on this, we present a real-time physics-based approach that generates natural and physically plausible motions for a highly complex task ball catching. We showed that ball catching behavior could be achieved with the proper combination of rather simple motor skills, such as standing, walking, and reaching. The character learns some policies to know how and when to react by using reinforcement learning in order to use time accurately. We demonstrate the effectiveness of our method with some of the catching animation results in different catching strategies. Copyright (c) 2015John Wiley & Sons, Ltd.