Written by two of Europe's leading robotics experts, this book provides the tools for a unified approach to the modelling of robotic manipulators, whatever their mechanical structure. No other ...publication covers the three fundamental issues of robotics: modelling, identification and control. It covers the development of various mathematical models required for the control and simulation of robots.
· World class authority· Unique range of coverage not available in any other book· Provides a complete course on robotic control at an undergraduate and graduate level
This article presents a holistic approach to the engineering of an artificial robot skin for robots. An example of a multimodal skin cell is given, one that supports multiple human-like sensing ...modalities, and support for skin cell network is also provided; this is essential to form large-area skin patches in order to cover the surfaces of robots. The essential elements of efficiently handling a large amount of tactile data are explained. A general control framework, which supports robots commanded in position, velocity, and torque, is provided and validated. Several applications of this robot skin will be presented, demonstrating the effectiveness and efficiency of our artificial robot skin to support a wide number of robotic platforms as well as its ease of use across different domains.
Unlike most control systems, kinematic uncertainty is present in robot control systems in addition to dynamic uncertainty. The use of different types of external sensors in various configurations ...also results in different sensory transformation or Jacobian matrices and thus leads to different kinematic models. Currently, there is no systematic theoretical framework in developing data-driven neural network (NN) learning and control methods for task-space tracking control of robots with unknown kinematics and dynamics. The existing NN controllers are limited to either dynamic control or kinematic control without considering the interaction between the inner control loop and the outer control loop. In this paper, a NN based data driven offline learning algorithm and an online learning controller are proposed, which are combined in a complementary way. The proposed task-space control algorithms can be implemented on robotic systems with closed control architecture by considering the interaction with the inner control loop. Theoretical analyses are presented to show the stability of the systems and experimental results are presented to illustrate the performance of the proposed learning algorithms.
Abstract This article describes the controlling of robot arm using different operations with choice. It is a programmable arm to hold and place the objects. Also it can change the position of the ...objects. The addition features are added to robotic arm using a reprogrammable FPGA mechanism. The robotic arm parts are jointed to give flexible move and rotate movements. We have used spartan3 FPGA to implement and test the robot arm conditions. We have used digital controlling inputs to control the robot arm directions.
The article proposes a method for solving the problem of predicting the self-collision of multi-link manipulators with their agreed work. The method is based on the analysis of projections of ...manipulator links on coordinate planes. The proposed approach will make it possible to solve the problem simple and suitable for the online prediction mode of critical positions of manipulators, possible self-collision, with their coordinated work. The developed algorithm was tested when constructing the control of an anthropomorphic robot SAR-400.
The article discusses the formulation of the problem of multicriteria design of a robotic system consisting of a group of robots, with the aim of achieving specified targets. A new approach to ...organizing the control of such robotic systems based on the partial dominance of decisions over target indicators is proposed. Illustrative examples of the application of the approach for UAV groups are given.
Accurate trajectory-tracking control for quadrotors is essential for safe navigation in cluttered environments. However, this is challenging in agile flights due to nonlinear dynamics, complex ...aerodynamic effects, and actuation constraints. In this article, we empirically compare two state-of-the-art control frameworks: the nonlinear-model-predictive controller (NMPC) and the differential-flatness-based controller (DFBC), by tracking a wide variety of agile trajectories at speeds up to 20 m/s (i.e., 72 km/h). The comparisons are performed in both simulation and real-world environments to systematically evaluate both methods from the aspect of tracking accuracy, robustness, and computational efficiency. We show the superiority of the NMPC in tracking dynamically infeasible trajectories, at the cost of higher computation time and risk of numerical convergence issues. For both methods, we also quantitatively study the effect of adding an inner loop controller using the incremental nonlinear dynamic inversion method, and the effect of adding an aerodynamic drag model. Our real-world experiments, performed in one of the world's largest motion capture systems, demonstrate more than 78% tracking error reduction of both NMPC and DFBC, indicating the necessity of using an inner loop controller and aerodynamic drag model for agile trajectory tracking.
A class of abstract aerial robotic systems is introduced, the laterally bounded force vehicles, in which most of the control authority is expressed along a principal thrust direction, while along the ...lateral directions a (smaller and possibly null) force may be exploited to achieve full-pose tracking. This class approximates platforms endowed with noncollinear rotors that can modify the orientation of the total thrust in a body frame. If made possible by the force constraints, the proposed SE(3)-based control strategy achieves the independent tracking of position-plus-orientation trajectories. The method, which is proven using a Lyapunov technique, deals seamlessly with both underactuated and fully actuated platforms, and guarantees at least the position tracking in the case of an unfeasible full-pose reference trajectory. Several experimental tests are presented that clearly show the approach practicability and the sharp improvement with respect to state of the art.
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