Parallel formulation of the inverse kinematics of modular hyper-redundant manipulators

A method is presented for generating inverse kinematic solutions for hyper-redundant manipulators of fixed or variable length. This method uses a continuous backbone curve to capture the macroscopic geometric features of the manipulator. The inverse kinematics of the backbone curve can be used directly to specify the geometry of a wide variety of hyper-redundant manipulator morphologies. The hyper-redundant manipulators are broken nonredundant segments which have closed form inverse kinematic solutions. The kinematic constraints for each segment are specified independently by the backbone curve, and the kinematics of the total manipulator can therefore be solved in parallel. The method is demonstrated with planar and spatial variable geometry truss manipulators

A General Numerical Method for Hyper-Redundant Manipulator Inverse Kinematics

Hyper-redundant robots have a very large or infinite degree of kinematic redundancy. A generalized resolved-rate technique for solving hyper-redundant manipulator inverse kinematics using a backbone curve is introduced. This method is applicable even in cases when explicit representation of the backbone curve intrinsic geometry cannot be written in closed form. Problems of end-effector trajectory tracking which were previously intractable can now be handled with this technique. Examples include configurations generated using the calculus of variations. The method is naturally parallelizable for fast digital and/or analog computation

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

Kinematically optimal hyper-redundant manipulator configurations

“Hyper-redundant” robots have a very large or infinite degree of kinematic redundancy. This paper develops new methods for determining “optimal” hyper-redundant manipulator configurations based on a continuum formulation of kinematics. This formulation uses a backbone curve model to capture the robot's essential macroscopic geometric features. The calculus of variations is used to develop differential equations, whose solution is the optimal backbone curve shape. We show that this approach is computationally efficient on a single processor, and generates solutions in O(1) time for an N degree-of-freedom manipulator when implemented in parallel on O(N) processors. For this reason, it is better suited to hyper-redundant robots than other redundancy resolution methods. Furthermore, this approach is useful for many hyper-redundant mechanical morphologies which are not handled by known methods

Simulated and experimental results of dual resolution sensor based planning for hyper-redundant manipulators

This paper presents a dual-resolution local sensor based planning method for hyper-redundant robot mechanisms. Two classes of sensor feedback control methods, working at different sampling rates and different spatial resolutions, are considered: full shape modification (FSM), and partial shape modification (PSM). FSM and PSM cooperate to utilize a mechanism's hyper-redundancy to enable both local obstacle avoidance and end-effector placement in real-time. These methods have been implemented on a thirty degree of freedom hyper-redundant manipulator which has 11 ultrasonic distance measurement sensors and 20 infrared proximity sensors. The implementation of these algorithms in a dual CPU real-time control computer, an innovative sensor bus architecture, and a novel graphical control interface are described. Experimental results obtained using this test bed show the efficacy of the proposed method