A modal approach to hyper-redundant manipulator kinematics
This paper presents novel and efficient kinematic modeling techniques for "hyper-redundant" robots. This approach is based on a "backbone curve" that captures the robot's macroscopic geometric features. The inverse kinematic, or "hyper-redundancy resolution," problem reduces to determining the time varying backbone curve behavior. To efficiently solve the inverse kinematics problem, the authors introduce a "modal" approach, in which a set of intrinsic backbone curve shape functions are restricted to a modal form. The singularities of the modal approach, modal non-degeneracy conditions, and modal switching are considered. For discretely segmented morphologies, the authors introduce "fitting" algorithms that determine the actuator displacements that cause the discrete manipulator to adhere to the backbone curve. These techniques are demonstrated with planar and spatial mechanism examples. They have also been implemented on a 30 degree-of-freedom robot prototype.
© 1994 IEEE. Reprinted with permission. Manuscript received March 24, 1992; revised March 26, 1993. This work was sponsored by National Science Foundation grant #MSS-901779; NSF Presidential Young Investigator award #MSS-9157843; by the Office of Naval Research Young Investigator Award N00014-92-J1920; and by a NASA Graduate Student Researchers Program fellowship (for the first author).
Published - CHIieeetra94.pdf