Guided Self-organisation for Autonomous Robot Development

The paper presents a method to guide the self-organised development of behaviours of autonomous robots. In earlier publications we demonstrated how to use the homeokinesis principle and dynamical systems theory to obtain self-organised playful but goal-free behaviour. Now we extend this framework by reinforcement signals. We validate the mechanisms with two experiment with a spherical robot. The first experiment aims at fast motion, where the robot reaches on average about twice the speed of a not reinforcement robot. In the second experiment spinning motion is rewarded and we demonstrate that the robot successfully develops pirouettes and curved motion which only rarely occur among the natural behaviours of the robot.

[1]  Ralf Der,et al.  Let it roll - Emerging Sensorimotor Coordination in a Spherical Robot , 2006 .

[2]  R. Der,et al.  True autonomy from self-organized adaptivity , 2002 .

[3]  Jürgen Schmidhuber,et al.  Completely Self-referential Optimal Reinforcement Learners , 2005, ICANN.

[4]  Nuttapong Chentanez,et al.  Intrinsically Motivated Reinforcement Learning , 2004, NIPS.

[5]  Ralf Der,et al.  From Motor Babbling to Purposive Actions: Emerging Self-exploration in a Dynamical Systems Approach to Early Robot Development , 2006, SAB.

[6]  Ralf Der,et al.  Homeokinetic approach to autonomous learning in mobile robots , 2002 .

[7]  Ralf Der,et al.  Rocking Stamper and Jumping Snakes from a Dynamical Systems Approach to Artificial Life , 2006, Adapt. Behav..

[8]  Pierre-Yves Oudeyer,et al.  The Playground Experiment: Task-Independent Development of a Curious Robot , 2005 .

[9]  Ralf Der Self-organized acquisition of situated behaviors , 2001 .

[10]  E. D. Paolo,et al.  Organismically-inspired robotics: homeostatic adaptation and teleology beyond the closed sensorimotor loop , 2003 .

[11]  James L. McClelland,et al.  Autonomous Mental Development by Robots and Animals , 2001, Science.

[12]  Ralf Der,et al.  Homeokinesis - A new principle to back up evolution with learning , 1999 .

[13]  Jon Timmis,et al.  Once More Unto the Breach: Towards Artificial Homeostasis? , 2005 .

[14]  山田 祐,et al.  Open Dynamics Engine を用いたスノーボードロボットシミュレータの開発 , 2007 .

[15]  M. Mohammadian Computational Intelligence for Modelling, Control and Automation '99 , 1999 .

[16]  Leandro Nunes de Castro,et al.  Recent Developments In Biologically Inspired Computing , 2004 .

[17]  Giulio Sandini,et al.  Developmental robotics: a survey , 2003, Connect. Sci..

[18]  John Hallam,et al.  From Animals to Animats 10 , 2008 .