Kamen Delchev

This paper represents the development of a prototype robotic system for automatic bone drilling in orthopaedic surgery. A new design of the mechanical structure is proposed, answering the surgical requirements for the robot dimensions and weight to be as small as possible. The new structure design is based on idea of parallelism of the axis of the linear actuator and the axis of the rotary one. The control system is improved by using a new micro-controller. A new type of linear drive and a new force sensor (load cell) are built in, so that the quality characteristics of the “Orthopaedic bone Drilling Robot” (ODRO) are not only the same as previous its two versions, but becomes better. An experimental setup is arranged and experiments are executed to test and to verify the robot quality features and functional capabilities.

Bone drilling manipulation often occurs in the orthopaedic surgery. By statistics, nowadays, about one million people only in Europe need such an operation every year, where bone implants are inserted. Almost always, the drilling is performed handily, which cannot avoid the subjective factor influence. The question of subjective factor reduction has its answer - automatic bone drilling. The specific features and problems of orthopaedic drilling manipulation are considered in this work. The automatic drilling is presented according the possibilities of robotized system Orthopaedic Drilling Robot (ODRO) for assuring the manipulation accuracy, precision, reliability and safety.

SUMMARY: This paper presents a model‐based nonlinear iterative learning control (NILC) for nonlinear multiple‐input and multiple‐output mechanical systems of robotic manipulators. An algorithm of a new strategy for the NILC implementation is proposed. This algorithm ensures that trajectory‐tracking errors of the proposed NILC, when implemented, are bounded by a given error norm bound. Both standard and bounded‐error learning control laws with feedback controllers attached are considered. The NILC synthesis is based on a dynamic model of a six degrees of freedom robotic manipulator. The dynamic model includes viscous and Coulomb friction and input generalized torques are bounded. With respect to the bounded‐error and standard learning processes applied to a virtual PUMA 560 robot (Unimation, Inc. Danburry, CT, USA), simulation results are presented in order to verify maximal tracking errors, convergence and applicability of the proposed learning control. Copyright © 2013 John Wiley & Sons, Ltd.

Bone drilling and cutting manipulations are widespread in the orthopedic surgery. In free hand performance of them some errors such as an inaccurate penetration and dilate of bone hole, overheating, harm soft tissues could be occurring. The goal of this study is to design and develop control concept for a bone drilling and cutting robotized system. The proposed orthopedic system consists of two executive modules for drilling and cutting and common control panel. The control algorithms and programs for drilling have done and given in the paper. We are developing the control algorithms for cutting manipulation.

This paper deals with a simulation-based design of model-based iterative learning control (ILC) for multi-input, multi-output nonlinear time-varying systems. The main problem of the implementation of the nonlinear ILC in practice is possible inadmissible transient growth of the tracking error due to a non-monotonic convergence of the learning process. A model-based nonlinear closed-loop iterative learning control for robot manipulators is synthesized and its tuning depends on only four positive gains of both controllers - the feedback one and the learning one. A simulation-based approach for tuning the learning and feedback controllers is proposed to achieve fast and monotonic convergence of the presented ILC. In the case of excessive growth of transient errors this approach is the only way for learning gains tuning by using classical engineering techniques for practical online tuning of feedback gains

The paper deals with computer simulation and synthesis of learning trajectory-tracking robot control based on the explicit form dynamic equations. Robots with inaccurate inertia parameters are considered. Two learning operators are proposed. The simplified one is a scalar function identical to the minimal eigenvalue of the inertial matrix of the dynamic equations. The complicated one is the inertial matrix itself. The learning operators are the basis of two learning-control laws, both with a feedback controller attached. For comparison of the results, a computer model of a virtual (test) robot with precise inertia parameters is assumed. The convergence of the learning procedure for both control laws proposed is examined by computer dynamics simulation of the resulting trajectory-tracking motion of the virtual robot. In spite of significant initial trajectory-tracking errors, good convergence of the learning procedures is achieved. The results are promising when the learning operator is in compliance with the robot inertial matrix.

The present paper discusses the problems of planning and optimization of maneuver (reorientation) strategies of large-space flexible structures as long booms and tethered satellites subject to conditions for minimization of deviations and vibrations. An approach based on the multibody system methodology for dynamics simulation and forward analysis is proposed. The optimization problem is defined as nonlinear programming problem. Iterative procedure based on directional derivatives and consequential dynamic analysis is applied. Polynomial approximation of the input motion is used, its coefficient being changed using optimization techniques. The principle for minimization of the total energy of the deformable system is applied in an algorithm for planning of controlled motion and computation of driving forces of the actuators. Admissible velocities of the maneuvers are estimated. The process of exaggeration of high order vibrations is analyzed. Examples of maneuver implementation of extremely flexible tethered satellite and suppression of vibrations are presented.