Combining Central Pattern Generators with the Electromagnetism-like Algorithm for Head Motion Stabilization during Quadruped Robot Locomotion

Visually-guided locomotion is important for autonomous robotics. However, there are several difficulties, for instance, the head shaking that results from the robot locomotion itself that constraints stable image acquisition and the possibili ty to rely on that information to act accordingly. In this ar ticle, we propose a controller architecture that is able to generate locomotion for a quadruped robot and to generate head motion able to minimizethe head motion induced by locomotion itself. The movement controllers are biologically inspired in the concept of Central Pattern Generators (CPGs). CPGs are modelled based on nonlinear dynamical systems, coupled Hopf oscill ators. This approach allows to explicitly specify parameters such as ampli tude, offset and frequency of movement and to smoothly modulate the generated oscill ations according to changes in these parameters. We take advantage of this par ticular ity and propose a combined approach to generate head movement stabili zation on a quadruped robot, using CPGs and a global optimization algor ithm. The best set of parameters that generates the head movement are computed by the electromagnetism-like algor ithm in order to reduce the head shaking caused by locomotion. Experimental resultson a simulated AIBO robot demonstrate that the proposed approach generates head movement that does not eliminate but reduces the one induced by locomotion. I . INTRODUCTION Robot locomotion is a challenging task that involves several relevant subtasks, not yet completely solved. The motion of quadruped, biped and snake-like robots, for instance, with cameras mounted in their heads, causes head shaking.This kind of disturbances, generated by locomotion itself, makes it difficult to keep the visual frame stable and, therefore, to act according to the visual information. Head stabili zation isvery important for achievingavisually-guided locomotion, a concept which has been suggested from a considerable number of neuroscientific findings in humans and animals [18]. As a basic research to realize visually-guided quadruped locomotion, we aim in this article at head stabili zation of a quadruped robot that walks with a walking gait. In our research, we propose a motion stabili zation system of an ers-7 AIBO quadruped robot, which performs its own head motion according to a feedforward controller. Several similar works have been proposed in literature [4], [7], [6], [5]. Cristina Santos, Miguel Oliveira and Vitor Matos are with Industrial Electronics Department, School of Engineering, University of Minho, 4800-058 Guimaraes, Portugal cristina@dei.uminho. pt, mcampos@dei.uminho. pt, vmatos@dei.uminho. pt Ana Rocha and Lino Costa are with Production Systems Department, School of Engineering, University of Minho, 4710-057 Braga, Portugal arocha@dps.uminho. pt, lac@dps.uminho. pt But these methods consider that the robot moves according to a scheduled robot motion plan, which imply that space and time constraints on robot motion must be known before hand as well as robot and environment models. As such, control is based on this scheduled plan. Other works have successfully achieved gazestabili zation [5], that consists on image stabili zation during head movements in space. The overall of the gazestabili zation approaches can be divided into two types of techniques. One uses specific hardware, like accelerometersand gyroscopeto estimate the3D posture of the head, and complex control algorithms to compensate the oscill ations. The use of inertial information was already proposed by several authors [5], [16], [17]. Typically this kind of techniques is used in binocular robot heads, where gazeis implemented throughthe coordination of the two eye movements. Most of the approachesare inspired in biological systems, specifically in the human Vestibular-Ocular Reflex (VOR). In robotswith fixed eyes, thefixation point procedure isachieved bycompensatory head or bodymovements, based on multisensory information of the head. In this work, a combined approach to generate head movement stabili zation ona quadruped robot, using Central Pattern Generators (CPGs) and the electromagnetism-like algorithm is proposed. We intend to use a head controller, based on Central Pattern Generators (CPGs), that generates trajectories for tilt , pan and nod head joints. CPGs are neural networks located in the spine of vertebrates, able to generate coordinated rhythmic movements, namely locomotion [11]. These CPGs are modelled as coupled oscill ators and solved using numeric integration. These CPGs have been applied in drumming [1] and postural control [3]. This dynamical systems approach model for CPGs presents multiple interesting properties, including: low computation cost which is well suited for real time; robustness against small perturbations; thesmooth onlinemodulation of trajectories throughchanges in the dynamical systems parameters and phase-locking between the different oscill ators for different DOFs. In order to achieve the desired head movement, opposed to the one induced by locomotion, it is necessary to appropriately tune the CPG parameters. This can be achieved by optimizing the CPG parameters using an optimization method. The optimization process is done offline according to the head movement induced by the locomotion when no stabili zation procedure was performed. Some algorithms for solving this type of problem require substantial gradient information and aim to improve the 2nd International Workshop on Evolutionary and Reinforcement Learning for Autonomous Robot Systems (ERLARS 2009) St. Louis, Missouri, USA, October 15 2009