Generalized Inverse Kinematics for N-DOF Robots

An intelligent robot must have the ability to make choices based on a finite number of physical pathways. These redundant robots can often perform the same task in and infinite variety of ways and decision making must be employed to choose the best option. Intelligent robots of the future will have a large degree of redundancy and make decisions based on a wide variety of sensory information and operational constraints. Consequently, decision-making software is being developed to interpret the sensory input and allocate resources based on task independent criteria in order to maximize system performance. 

Given the model of a robot system, it is possible to define performance criteria, by which operational characteristics inherent to to robot may be analyzed. These mathematically rigorous performance measures may be used to determine the comparative quality of specific configurations, as the criteria provide insight into the robot's complex geometric and physical properties. The information obtained may be used to make decisions regarding the management of the robot's resources. For example, these values give insight into characteristics such as proximity to singularities, force transmission potential, and compliance. The performance criteria include kinematic: based on first and second-order geometric properties of the manipulator structure, inertial: based on the geometric coupling in the manipulator's dynamic equations, kinetic energy: based on system level kinetic energy distribution properties of the individual links, compliance: based on the link and joint compliances of the manipulator structure.

A general approach to the inverse kinematics problem is required to interpret the criteria information while choosing the desired join-level trajectory for the robot. The goal is to position the robot in a kinematic configuration which maximizes the performance of the task by the manipulator in real time. A general approach to the inverse kinematics problem must apply to all robots, allow for the incorporation of unlimited performance criteria and provide a balance between task planning requirements and manipulator performance of the task. The approach is called generalized inverse kinematics since system performance criteria may be considered. By not restricting the approach to simple robot geometries, this work applies to redundant robots and hyper-redundant "snake" type robots as well as the common industrial variety of robot.