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John Hollerbach

John Hollerbach is an Associate Professor in the MIT Department of Brain and Cognitive Sciences and the MIT Artificial Intelligence Laboratory.

Titles by This Author

Model-Based Control of a Robot Manipulator presents the first integrated treatment of many of the most important recent developments in using detailed dynamic models of robots to improve their control. The authors' work on automatic identification of kinematic and dynamic parameters, feedforward position control, stability in force control, and trajectory learning has significant implications for improving performance in future robot systems. All of the main ideas discussed in this book have been validated by experiments on a direct-drive robot arm.

The book addresses the issues of building accurate robot models and of applying them for high performance control. It first describes how three sets of models—the kinematic model of the links and the inertial models of the links and of rigid-body loads—can be obtained automatically using experimental data. These models are then incorporated into position control, single trajectory learning, and force control. The MIT Serial Link Direct Drive Arm, on which these models were developed and applied to control, is one of the few manipulators currently suitable for testing such concepts.

Introduction. Direct Drive Arms. Kinematic Calibration. Estimation of Load Inertial Parameters. Estimation of Link Inertial Parameters. Feedforward and Computed Torque Control. Model-Based Robot Learning. Dynamic Stability Issues in Force Control. Kinematic Stability Issues in Force Control. Conclusion.

Model-Based Control of a Robot Manipulator is included in the Artificial Intelligence Series edited by Patrick Winston and Michael Brady.

Titles by This Editor

Planning and Control

The present surge of interest in robotics can be expected to continue through the 1980s. Major research efforts are springing up throughout industry and in the universities. Senior and graduate level courses are being developed or planned in many places to prepare students to contribute to the development of the field and its industrial applications. Robot Motion will serve this emerging audience as a single source of information on current research in the field.

The book brings together nineteen papers of fundamental importance to the development of a science of robotics. These are grouped in five sections: Dynamics; Trajectory Planning; Compliance and Force Control; Feedback Control; and Spatial Planning. Each section is introduced by a substantial analytical survey that lays out the problems that arise in that area of robotics and the approaches and solutions that have been tried, with an evaluation of their strengths and shortcomings. In addition, there is an overall introduction that relates robotics research to general trends in the development of artificial intelligence.

Individual papers are the work of H. Hanafusa, H. Asada, N. Hogan, M. T. Mason, R. Paul, B. Shimano, M. H. Raibert, J. J. Craig, R. H. Taylor, D. E. Whitney, J. M. Hollerbach, J. Luh, M. Walker, R. J. Popplestone, A. P. Ambler, I. M. Bellos, T. LozanoPerez, E. Freund, D. F. Golla, S. C. Garg, P. C. Hughes, and K. D. Young.

Robot Motion is included in the MIT Press Artificial Intelligence Series.