Richard Colbaugh

Bio: Richard Colbaugh is an academic researcher from Sandia National Laboratories. The author has contributed to research in topics: Adaptive control & Motion control. The author has an hindex of 26, co-authored 148 publications receiving 2368 citations. Previous affiliations of Richard Colbaugh include New Mexico State University & United States Department of Energy.

Force tracking in impedance control

Abstract: This article presents two simple on-line schemes for force tracking within the impedance-control framework. The force- tracking capability of impedance control is particularly important for providing robustness in the presence of large uncertainties or variations in environmental parameters. The two proposed schemes generate the reference position trajec tory required to produce a desired contact force despite lack of knowledge of the environmental stiffness and location. The first scheme uses direct adaptive control to generate the refer ence position on-line as a function of the force-tracking error. Alternatively, the second scheme utilizes an indirect adaptive strategy in which the environmental parameters are estimated on-line, and the required reference position is computed based on these estimates. In both schemes, adaptation allows au tomatic gain adjustment to provide a uniform performance despite variations in the environmental parameters. Simula tion studies are presented for a 7-DOF Robotics R...

Improved configuration control for redundant robots

Abstract: This article presents a singularity-robust task-prioritized reformulation of the configuration control scheme for redundant robot manipulators. This reformulation suppresses large joint velocities near singularities, at the expense of small task trajectory errors. This is achieved by optimally reducing the joint velocities to induce minimal errors in the task performance by modifying the task trajectories. Furthermore, the same framework provides a means for assignment of priorities between the basic task of end-effector motion and the user-defined additional task for utilizing redundancy. This allows automatic relaxation of the additional task constraints in favor of the desired end-effector motion, when both cannot be achieved exactly. The improved configuration control scheme is illustrated for a variety of additional tasks, and extensive simulation results are presented.

Force tracking in impedance control

Abstract: Two simple and computationally efficient schemes for force tracking using impedance control are presented. The schemes generate the reference position trajectory required to produce a desired contact force despite lack of knowledge of the environmental stiffness and location. The first scheme uses direct adaptive control to generate the reference position on-line as a function of the force tracking-error. The second scheme utilizes an indirect adaptive strategy in which the environmental parameters are estimated on-line, and the required reference position is computed based on these estimates. Simulation studies are presented for a 7-degrees-of-freedom (DOF) robotics research arm using full arm dynamics. It is shown that the adaptive schemes are able to compensate for uncertainties in both the environmental stiffness and location, so that the end-effector applies the desired contact force while exhibiting the specified impedance dynamics. >

Direct adaptive impedance control of robot manipulators

Abstract: This article presents an adaptive scheme for controlling the end-effector impedance of robot manipulators. The proposed control system consists of three subsystems: a simple “filter” that characterizes the desired dynamic relationship between the end-effector position error and the end-effector/environment contact force, an adaptive controller that produces the Cartesian-space control input required to provide this desired dynamic relationship, and an algorithm for mapping the Cartesian-space control input to a physically realizable joint-space control torque. The controller does not require knowledge of either the structure or the parameter values of the robot dynamics and is implemented without calculation of the robot inverse kinematic transformation. As a result, the scheme represents a general and computationally efficient approach to controlling the impedance of both nonredundant and redundant manipulators. Furthermore, the method can be applied directly to trajectory tracking in free-space motion by removing the impedance filter. Computer simulation results are given for a planar four degree-of-freedom redundant robot under adaptive impedance control. These results demonstrate that accurate end-effector impedance control and effective redundancy utilization can be achieved simultaneously by using the proposed controller.

Obstacle avoidance for redundant robots using configuration control

Abstract: A redundant robot control scheme is provided for avoiding obstacles in a workspace during motion of an end effector along a preselected trajectory by stopping motion of the critical point on the robot closest to the obstacle when the distance therebetween is reduced to a predetermined sphere of influence surrounding the obstacle. Algorithms are provided for conveniently determining the critical point and critical distance.

Neural Network Control of Robot Manipulators and Nonlinear Systems

Abstract: From the Publisher: This graduate text provides an authoritative account of neural network (NN) controllers for robotics and nonlinear systems and gives the first textbook treatment of a general and streamlined design procedure for NN controllers. Stability proofs and performance guarantees are provided which illustrate the superior efficiency of the NN controllers over other design techniques when the system is unknown. New NN properties, such as robustness and passivity are introduced, and new weight tuning algorithms are presented. Neural Network Control of Robot Manipulators and Nonlinear Systems provides a welcome introduction to graduate students, and an invaluable reference to professional engineers and researchers in control systems.

Robot Manipulator Control: Theory and Practice

Abstract: Robot Manipulator Control offers a complete survey of control systems for serial-link robot arms and acknowledges how robotic device performance hinges upon a well-developed control system. Containing over 750 essential equations, this thoroughly up-to-date Second Edition, the book explicates theoretical and mathematical requisites for controls design and summarizes current techniques in computer simulation and implementation of controllers. It also addresses procedures and issues in computed-torque, robust, adaptive, neural network, and force control. New chapters relay practical information on commercial robot manipulators and devices and cutting-edge methods in neural network control.

An Introduction to Game Theory

Abstract: This chapter is devoted to a more detailed examination of game theory. Game theory is an important tool for analyzing strategic behavior, is concerned with how individuals make decisions when they recognize that their actions affect, and are affected by, the actions of other individuals or groups. Strategic behavior recognizes that the decision-making process is frequently mutually interdependent. Game theory is the study of the strategic behavior involving the interaction of two or more individuals, teams, or firms, usually referred to as players. Two game theoretic scenarios were examined in this chapter: Simultaneous-move and multi-stage games. In simultaneous-move games the players effectively move at the same time. A normal-form game summarizes the players, possible strategies and payoffs from alternative strategies in a simultaneous-move game. Simultaneous-move games may be either noncooperative or cooperative. In contrast to noncooperative games, players of cooperative games engage in collusive behavior. A Nash equilibrium, which is a solution to a problem in game theory, occurs when the players’ payoffs cannot be improved by changing strategies. Simultaneous-move games may be either one-shot or repeated games. One-shot games are played only once. Repeated games are games that are played more than once. Infinitely-repeated games are played over and over again without end. Finitely-repeated games are played a limited number of times. Finitely-repeated games have certain or uncertain ends.

Adaptive Neural Impedance Control of a Robotic Manipulator With Input Saturation

Abstract: In this paper, adaptive impedance control is developed for an ${n}$ -link robotic manipulator with input saturation by employing neural networks. Both uncertainties and input saturation are considered in the tracking control design. In order to approximate the system uncertainties, we introduce a radial basis function neural network controller, and the input saturation is handled by designing an auxiliary system. By using Lyapunov’s method, we design adaptive neural impedance controllers. Both state and output feedbacks are constructed. To verify the proposed control, extensive simulations are conducted.