4,606 research outputs found
Robust Cooperative Manipulation without Force/Torque Measurements: Control Design and Experiments
This paper presents two novel control methodologies for the cooperative
manipulation of an object by N robotic agents. Firstly, we design an adaptive
control protocol which employs quaternion feedback for the object orientation
to avoid potential representation singularities. Secondly, we propose a control
protocol that guarantees predefined transient and steady-state performance for
the object trajectory. Both methodologies are decentralized, since the agents
calculate their own signals without communicating with each other, as well as
robust to external disturbances and model uncertainties. Moreover, we consider
that the grasping points are rigid, and avoid the need for force/torque
measurements. Load distribution is also included via a grasp matrix
pseudo-inverse to account for potential differences in the agents' power
capabilities. Finally, simulation and experimental results with two robotic
arms verify the theoretical findings
A survey on fractional order control techniques for unmanned aerial and ground vehicles
In recent years, numerous applications of science and engineering for modeling and control of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) systems based on fractional calculus have been realized. The extra fractional order derivative terms allow to optimizing the performance of the systems. The review presented in this paper focuses on the control problems of the UAVs and UGVs that have been addressed by the fractional order techniques over the last decade
AI based Robot Safe Learning and Control
Introduction This open access book mainly focuses on the safe control of robot manipulators. The control schemes are mainly developed based on dynamic neural network, which is an important theoretical branch of deep reinforcement learning. In order to enhance the safety performance of robot systems, the control strategies include adaptive tracking control for robots with model uncertainties, compliance control in uncertain environments, obstacle avoidance in dynamic workspace. The idea for this book on solving safe control of robot arms was conceived during the industrial applications and the research discussion in the laboratory. Most of the materials in this book are derived from the authors’ papers published in journals, such as IEEE Transactions on Industrial Electronics, neurocomputing, etc. This book can be used as a reference book for researcher and designer of the robotic systems and AI based controllers, and can also be used as a reference book for senior undergraduate and graduate students in colleges and universities
Physical Human-Robot Interaction Control of an Upper Limb Exoskeleton with a Decentralized Neuro-Adaptive Control Scheme
Within the concept of physical human-robot interaction (pHRI), the most
important criterion is the safety of the human operator interacting with a high
degree of freedom (DoF) robot. Therefore, a robust control scheme is in high
demand to establish safe pHRI and stabilize nonlinear, high DoF systems. In
this paper, an adaptive decentralized control strategy is designed to
accomplish the abovementioned objectives. To do so, a human upper limb model
and an exoskeleton model are decentralized and augmented at the subsystem level
to enable a decentralized control action design. Moreover, human exogenous
force (HEF) that can resist exoskeleton motion is estimated using radial basis
function neural networks (RBFNNs). Estimating both human upper limb and robot
rigid body parameters, along with HEF estimation, makes the controller
adaptable to different operators, ensuring their physical safety. The barrier
Lyapunov function (BLF) is employed to guarantee that the robot can operate in
a safe workspace while ensuring stability by adjusting the control law. Unknown
actuator uncertainty and constraints are also considered in this study to
ensure a smooth and safe pHRI. Then, the asymptotic stability of the whole
system is established by means of the virtual stability concept and virtual
power flows (VPFs) under the proposed robust controller. The experimental
results are presented and compared to proportional-derivative (PD) and
proportional-integral-derivative (PID) controllers. To show the robustness of
the designed controller and its good performance, experiments are performed at
different velocities, with different human users, and in the presence of
unknown disturbances. The proposed controller showed perfect performance in
controlling the robot, whereas PD and PID controllers could not even ensure
stable motion in the wrist joints of the robot
A survey on uninhabited underwater vehicles (UUV)
ASME Early Career Technical Conference, ASME ECTC, October 2-3, 2009, Tuscaloosa, Alabama, USAThis work presents the initiation of our underwater robotics research which will be focused on underwater
vehicle-manipulator systems. Our aim is to build an underwater vehicle with a robotic manipulator which has a robust system and also can compensate itself under the influence of the hydrodynamic effects. In this paper, overview of the existing underwater vehicle systems, thruster designs, their dynamic models and control architectures are given. The purpose and results of the existing methods in underwater robotics are investigated
Control strategies for robotic manipulators
This survey is aimed at presenting the major robust control strategies for rigid robot manipulators. The techniques discussed are feedback linearization/Computed torque control, Variable structure compensator, Passivity based approach and Disturbance observer based control. The first one is based on complete dynamic model of a robot. It results in simple linear control which offers guaranteed stability. Variable structure compensator uses a switching/relay action to overcome dynamic uncertainties and disturbances. Passivity based controller make use of passive structure of a robot. If passivity of a feedback system is proved, nonlinearities and uncertainties will not affect the stability. Disturbance observer based controllers estimate disturbances, which can be cancelled out to achieve a nominal model, for which a simple controller can then be designed. This paper, after explaining each control strategy in detail, finally compares these strategies for their pros and cons. Possible solutions to cope with the drawbacks have also been presented in tabular form. © 2012 IEEE
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