Browsing by Subject "Robots--Motion"
Now showing 1 - 2 of 2
Results Per Page
Sort Options
Item Influence of actuator parameters on performance capabilities of serial robotic manipulator systems(2008-08) Rios, Oziel, 1980-; Tesar, DelbertA serial robotic manipulator arm is a complex electro-mechanical system whose performance is primarily characterized by the internal parameters of its actuators. The actuator itself is a complex nonlinear system whose performance can be characterized by the speed and torque capabilities of its motor and its accuracy depends on the resolution of the encoder as well as its ability to resist deformations in its gear train under load. The mechanical gain associated with the gear train transmission is critical to the overall performance of the actuator since it amplifies the motor torque thus improving the force capability of the manipulator housing it, reduces the motor speed to a suitable output speed operating range, dominates the inertia content of the manipulator and amplifies the stiffness improving the precision under load of the overall system. In this work, a basic analytic process that can be used to manage the actuator parameters to obtain an improved arm design based on a set of desired/required performance specifications is laid out. The key to this analytic process is the mapping of the actuator parameters (motor speed, motor torque, rotary stiffness, encoder resolution, transmission efficiency, mass, rotary inertia) to their effective values at the system output via the mechanical gains of the actuator transmissions as well as the effective mechanical gains associated with the manipulator geometry. This forward mapping of the actuator parameters allows the designer to determine how each of the actuator parameters influences the functional capacity of the serial manipulator arm. The analytic formulation is demonstrated to be effective in addressing the issue of configuration management of serial robotic manipulators where the goal is to assemble a system from a finite set of actuator modules that meets some required performance specifications. To this end, four design case studies demonstrating the solution of the configuration management problem are presented where the application domains include designing for light to heavy-duty force applications, designing for responsiveness and designing for Human-Robot Interactions (HRI). The design trade-offs for each of the application domains are analyzed and design guidelines are presented. This research also formulates a new approach to characterizing the dynamic behavior of serial chain mechanisms via the kinetic energy distribution. In any mechanism, the amount of kinetic energy in the system is a very important quantity to analyze. Since the inertial torques are directly related to the rate of change of the kinetic energy, better design (and operation) is achieved by having an understanding of how kinetic energy is distributed along the mechanism structure as well as how rapidly kinetic energy is flowing within it. In this work, a description of the Kinetic Energy Partition Values (KEPV) for serial chain mechanisms, as well as their rates of change, are presented. The KEPVs arise from the partitioning of the mechanism’s kinetic energy. Two design criteria, one based on the KEPVs and another based on their rates of change, are developed. These design criteria are indicators of both the dynamic isotropy of the system as well as the amount of kinetic energy flow within the system. A six-axis spatial manipulator is used to illustrate the solution of a design optimization problem where the goal is to demonstrate how the inertial parameters of the actuators and mechanical gains of the actuator transmissions alter the kinetic energy of the system which is “measured” via an effective mass criterion and its distribution which is measured via the KEPV criterion. It is demonstrated that the mechanical gains in the actuators significantly influence the magnitude of the kinetic energy as well as its distribution within the system.Item Minimum distance influence coefficients for obstacle avoidance in manipulator motion planning(2002) Harden, Troy Anthony; Tesar, DelbertOne weakness of current robotic technology is motion planning. Current robots especially struggle to effectively operate in cluttered environments. In this report, first and second order influence coefficients for minimum distance magnitudes are developed. These coefficients provide fundamental analytics for rates of change of minimum distance magnitudes and allow for deeper insight into the interaction between a manipulator and its environment. They are also demonstrated as viable tools for use in manipulator obstacle avoidance. Influence coefficients are rigorously developed for three simple manipulator and workspace modeling primitives: a sphere, a cylisphere, and a quadrilateral plane. In addition, a general method to use for similar derivations for new modeling primitives is presented. Also, a comparison of the speed and accuracy of using finite differencing to calculate the second order coefficients instead of calculating them analytically is given. The developed influence coefficients provide extraordinary insight into the interactions between a robot and its environment because they isolate the geometry of the distance functions from system inputs (manipulator joint commands). As a demonstration of potential uses of these coefficients, twelve obstacle avoidance criteria based on minimum distances and artificial forces are developed and demonstrated using criteria-based inverse kinematics on a ten degree of freedom manipulator operating around three obstacles. In the demonstration, the zeroth and first order criteria run at an average rate of 1042 hertz and the second order criteria run at an average rate of 2.045 hertz. Using the developed criteria one at a time, the manipulator successfully completed a demanding end-effector path, 5200 setpoints in length, for many of the criteria. In some cases, using higher-order criteria improved manipulator performance. None of the criteria allowed the manipulator to strike the obstacles. This research successfully demonstrates the usefulness of first and second order influence coefficients for minimum distance magnitudes in solving the obstacle avoidance motion-planning problem. The obstacle avoidance results also point to the feasibility of using the developed coefficients to solve a wide range of additional motion-planning problems that focus on how a system interacts with its environment.