Reciprocal excitation between biological and robotic research

Stefan Schaal, Dagmar Sternad, William Dean, Shinya Kotosaka, Rieko Osu, Mitsuo Kawato, Gerard T. McKee, Paul S. Schenker
2000 Sensor Fusion and Decentralized Control in Robotic Systems III  
While biological principles have inspired researchers in computational and engineering research for a long time, there is still rather limited knowledge flow back from computational to biological domains. This paper presents examples of our work where research on anthropomorphic robots lead us to new insights into explaining biological movement phenomena, starting from behavioral studies up to brain imaging studies. Our research over the past years has focused on principles of trajectory
more » ... on with nonlinear dynamical systems, on learning internal models for nonlinear control, and on advanced topics like imitation learning. The formal and empirical analyses of the kinematics and dynamics of movements systems and the tasks that they need to perform lead us to suggest principles of motor control that later on we found surprisingly related to human behavior and even brain activity. Formalization of PPGs In order to accommodate discrete and rhythmic movements, two kinds of PPGs are needed, a point attractive PPG and a limit cycle PPG. Although it is possible to construct nonlinear differential equations that could realize both these behaviors in one set of equations (e.g., [25] ), for reasons of robustness, simplicity, functionality, and biological realism, we chose an approach that separates these two regimes. Every degree-of-freedom (DOF) of a limb is described by two variables, a rest position θ o and a superimposed oscillatory position, θ r , as shown in Figure 1 . By moving the rest position, discrete motion is generated. The change of rest position can be anchored in joint space or, by means of inverse kinematics transformations, in external space. In contrast, the rhythmic movement is produced in joint space, relative to the rest position. This dual strategy permits to exploit two different coordinate systems: joint space, which is the most efficient for rhythmic movement, and external (e.g., Cartesian) space, which is needed to reference a task to the external world. For example, it is now possible to bounce a ball on a racket by producing an oscillatory up-and-down movement in joint space, but using the discrete system to make sure the oscillatory movement remains under the ball such that the task can be accomplished-this task actually motivated our current research ([26]).
doi:10.1117/12.403706 fatcat:aie2gyf7rjexhge5hj4zwzhaam