Skill learning based catching motion control

نویسندگان

  • Gökçen Çimen
  • Zümra Kavafoglu
  • Ersan Kavafoglu
  • Tolga K. Çapin
  • Hasmet Gürçay
چکیده

SKILL LEARNING BASED CATCHING MOTION CONTROL Gökçen Çimen M.S. in Computer Engineering Supervisor: Assist. Prof. Dr. Tolga Kurtuluş Çapın July, 2014 In real world, it is crucial to learn biomechanical strategies that prepare the body in kinematics and kinetics terms during the interception tasks, such as kicking, throwing and catching. Based on this, we presents a real-time physics-based approach that generate natural and physically plausible motions for a highly complex taskball catching. We showed that ball catching behavior as many other complex tasks, can be achieved with the proper combination of rather simple motor skills, such as standing, walking, reaching. Since learned biomechanical strategies can increase the conscious in motor control, we concerned several issues that needs to be planned. Among them, we intensively focus on the concept of timing. 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 by presenting some of the catching animation results executed in different catching strategies.In each simulation, the balls were projected randomly, but within a interval of limits, in order to obtain different arrival flight time and height conditions.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Representation of robot motion control skill

Development of skilled robotics draws clues from model-based theories of human motor control. Thus, a comprehensive anthropomorphic background is given in the introductory part of the paper. Skills in robotics are viewed as a tool for fast and efficient real-time control that can handle complexity and nonlinearity of robots, generally aiming at robot autonomy. Particularly, a skill of redundanc...

متن کامل

Vision-Based Online Trajectory Generation and Its Application to Catching

In this paper a method for sensor-based online trajectory generation is proposed. This method is based on a nonlinear mapping from sensor information to a desired trajectory, and a nonlinear mapping is decided by online learning based on constraints of dynamics and kinematics. This method is applied to a catching task, and responsive and flexible motion is realized based on realtime high-speed ...

متن کامل

Towards Robust Skill Generalization: Unifying Learning from Demonstration and Motion Planning

In this paper, we present Combined Learning from demonstration And Motion Planning (CLAMP) as an efficient approach to skill learning and generalizable skill reproduction. CLAMP combines the strengths of Learning from Demonstration (LfD) and motion planning into a unifying framework. We carry out probabilistic inference to find trajectories which are optimal with respect to a given skill and al...

متن کامل

Robotic catching using a direct mapping from visual information to motor command

In this paper a robotic catching algorithm based on a nonlinear mapping of visual information to the desired trajectory is proposed. The nonlinear mapping is optimized by learning based on constraints of dynamics and kinematics. As a result a reactive and flexible motion is obtained owing to real-time high-speed visual information. Experimental results on catching a moving object using a high-s...

متن کامل

Role of feedback in the accuracy of perceived direction of motion-in-depth and control of interceptive action

We quantified the accuracy of the perception of the absolute direction of motion-in-depth (MID) of a simulated approaching object using a perceptual task and compared those data with the accuracy of estimating the passing distance measured by means of a simulated catching task. For the simulated catching task, movements of the index finger and thumb of the observer's hand were tracked as partic...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Journal of Visualization and Computer Animation

دوره 26  شماره 

صفحات  -

تاریخ انتشار 2015