Search results

The purpose of this paper is to propose an adaptive control for a redundant robot manipulator interacting physically with the environment, especially with the existence of humans, on its body.

The redundant properties of the robot manipulator are used and a reference velocity variable is introduced to unify the operation-space tracking control and the null-space impedance control under one common framework. Neural networks are constructed to deal with unstructured and unmodeled dynamic nonlinearities. Lyapunov function is used during the course of control design and simulation studies are carried out to further illustrate the effectiveness of the proposed strategies.

Satisfying tracking performance in the operation-space and compliance behavior in the null-space of the redundant robot manipulator are ensured simultaneously.

The design procedure of redundant robot manipulators control can be greatly simplified, and the framework of multi-priority control can be transformed into a joint-space velocity tracking problem via the introducing of a reference velocity variable.

The purpose of this paper is to present a dual-mode online optimization method (OOM) for trajectory tracking of the redundant manipulators. This method could be used to resolve the problem of the kinematics redundancy effectively when the manipulator moves in a limited space or its movements go through a singular point.

In the proposed method, the physical limits of the manipulator in the torque level is considered as inequality constraints for the optimal scheme. Besides, a dual-mode optimal scheme is developed to yield a feasible input in each control period during the path tracking task of the manipulator, especially when it moves under the limited space or around the singular point. Then, the scheme is formulated as a quadratic programming; the computationally efficient quadratic programming solver based on interior method is formulated to solve the kinematic redundancy problem.

The traditional pseudo inverse method (PIM) for the kinematic resolution to the redundant manipulator has some limitations, such as slow computation speed, unable to take joint physical limits into consideration, etc. Relatively, the OOM could be used to conquer the deficits of the PIM method. Combining with the dual-mode optimal scheme and considering the physical constraints in the torque level, the online method proposed in this paper is more robust and efficient than the existing method.

In this paper, dual-mode OOM is first proposed for the resolution of the kinematics redundancy problem. Specific design of its model and the discussion of its performance are also presented in this paper.

This paper aims to present an adaptive fuzzy sliding mode controller with nonlinear observer (AFSMCO) for the redundant robotic manipulator handling a varying payload to achieve a precise trajectory tracking in the task space. This approach could be applied to solve the problems caused by the dynamic effect of the varying payload to robotic system caused by model uncertainties.

First, a suitable observer using the recursive algorithm is presented for an accurate estimation of external disturbances caused by a variable payload. Second, the adaptive fuzzy logic is designed to approximate the parameters of the sliding mode controller combined with nonlinear observer (SMCO) to avoid chattering in real time. Moreover, Lyapunov theory is applied to guarantee the stability of the proposed closed-loop robotic system. Finally, the effectiveness of the proposed control approach and theoretical discussion are proved by simulation results on a seven-link robot and demonstrated by a humanoid robot platform.

The varying payload leads to large variations in the dynamics of the manipulator and the tracking error. To achieve high-precision position tracking, nonlinear observer was introduced to feed into the sliding mode control (SMC) which had improved the ability to resist the external disturbance. In addition, the chattering caused by the SMC was eliminated by recursively approximating the switching gain with the usage of adaptive fuzzy logic. Therefore, a distributed control strategy solves the problems of an SMC implementation in improving its tracking performance and eliminating the chattering of the system control.

The AFSMCO is proposed for the first time and used to control the redundant robotic manipulator that handles the varying payload. The proposed control algorithm possesses better robustness and higher precision for the trajectory tracking than classical SMC.

The purpose of this paper is to present the design and implementation of a zero‐initial‐velocity self‐motion scheme on a six degrees of freedom (six‐DOF) planar robot manipulator.

In view of the existence of physical limits in an actual robot manipulator, both joint‐angle limits and joint‐velocity limits are initially incorporated into the proposed self‐motion scheme for practical purposes. The proposed self‐motion scheme is then reformulated as a quadratic program (QP) and resolved at the joint‐velocity level. By combining the zero‐initial‐velocity constraint, the resultant QP can prevent the occurrence of a large initial joint velocity. Finally, based on the conversion technique of QP to a linear variational inequality, a numerical computing algorithm is presented to solve the QP and the corresponding self‐motion scheme.

The proposed zero‐initial‐velocity self‐motion scheme eliminates the phenomenon of the abrupt and drastic increase in joint velocity at the beginning of the self‐motion task execution. Simulative and experimental results based on a practical six‐DOF planar robot manipulator further verify the realizability, effectiveness and accuracy of the proposed self‐motion scheme. Based on the simulative results, the joint angle and the joint velocity meet the joint physical constraints.

The paper provides effective methods for handling the physical limits, the design of zero‐initial velocity, and the conversion from joint angle and joint velocity to motor‐driving pulses. Thus, the effective and safe self‐motion control of a manipulator is realized.

The paper describes the design and implementation of a zero‐initial‐velocity self‐motion scheme.

Most of the redundant dual-arm robots are singular free, dexterous and collision free compared to other robotic arms. This paper aims to analyse the workspace of redundant arms to study the manipulability. Furthermore, multi-layer perceptron (MLP) algorithm is used to determine the various joint parameters of both the upper body redundant arms. Trajectory planning of robotic arms is carried out with the help of inverse solutions obtained from the MLP algorithm.

In this paper, the kinematic equations are derived from screw theory approach and inverse kinematic solutions are determined using MLP algorithm. Levenberg–Marquardt (LM) and Bayesian regulation (BR) techniques are used as the backpropagation algorithms. The results from two backpropagation techniques are compared for determining the prediction accuracy. The inverse solutions obtained from the MLP algorithm are then used to optimize the cubic spline trajectories planned for avoiding collision between arms with the help of convex optimization technique. The dexterity of the redundant arms is analysed with the help of Cartesian workspace of arms.

Dexterity of redundant arms is analysed by studying the voids and singular spaces present inside the workspace of arms. MLP algorithms determine unique solutions with less computational effort using BR backpropagation. The inverse solutions obtained from MLP algorithm effectively optimize the cubic spline trajectory for the redundant dual arms using convex optimization technique.

Most of the MLP algorithms used for determining the inverse solutions are used with LM backpropagation technique. In this paper, BR technique is used as the backpropagation technique. BR technique converges fast with less computational time than LM method. The inverse solutions of arm joints for traversing optimized cubic spline trajectory using convex optimization technique are computed from the MLP algorithm.

The aim of this paper is to develop a redundancy‐resolution (RR) algorithm to optimize the joint space trajectory of the six‐rotation‐axis industrial robot as performing arc‐welding tasks.

The rotation of the tool around its symmetry axis is clearly irrelevant to the view of the task to be accomplished besides some exceptional situations. When performed with a general 6‐degrees‐of‐freedom (DOF) manipulator, there exists one DOF of redundancy that remains. By taking advantage of the symmetry axis of the welding electrode, the authors decompose the required instantaneous twist of the electrode into two orthogonal components, one lying into the relevant task subspace and one into the redundant task subspace, respectively. Joint‐limits and singularity avoidance are considered as the optimization objectives.

The twist‐decomposition algorithm is able to optimize effectively the joint space trajectory. It has been tested and demonstrated in simulation.

A new RR algorithm is introduced for the six‐rotation‐axis industrial robot performing welding tasks. A new kinetostatic performance index is proposed on evaluating the kinematic quality of robotic postures. It can also be used in other applications like milling, deburing and many other tasks requiring less than 6‐DOF in tool frame.

This paper aims to propose an innovative kinematic control algorithm for redundant robotic manipulators. The algorithm takes advantage of a bio-inspired approach.

A simplified two-degree-of-freedom model is presented to handle kinematic redundancy in the x-y plane; an extension to three-dimensional tracking tasks is presented as well. A set of sample trajectories was used to evaluate the performances of the proposed algorithm.

The results from the simulations confirm the continuity and accuracy of generated joint profiles for given end-effector trajectories as well as algorithm robustness, singularity and self-collision avoidance.

This paper shows how to control a redundant robotic arm by applying human upper arm-inspired concept of inter-joint dependency.

The purpose of this paper is to examine a new idea of vibration control which minimizes joint‐torques and suppresses vibration of the flexible redundant manipulator.

Using the kinematics redundancy feature of the flexible redundant manipulator, the self‐motion in the joint space can be properly chosen to both suppress vibration and minimize joint‐torques.

The study shows that the flexible redundant manipulator still has the second optimization feature on the premise of vibration suppression. The second optimization feature can be used to minimize joint‐torques on the premise of vibration suppression.

To a flexible redundant manipulator, its joint‐torques and vibration can be reduced simultaneously via its kinematics redundancy feature.

The method and algorithm discussed in the paper can be used to minimize joint‐torques and suppress vibration for the flexible redundant manipulator.

The paper contributes to the study on improving dynamic performance of the flexible redundant manipulator via its kinematics redundancy feature. The second optimization capability of the flexible redundant manipulator is discovered and used to both minimize joint‐torques and suppress vibration.

The purpose of this paper is to present a new method to establish a kinematic model for a continuum manipulator, whose end can be controlled to move in a three-dimensional workspace. A continuum manipulator has significant advantages over traditional, rigid manipulators in many applications because of its ability to conform to the environment. Moreover, because of its excellent flexibility, light weight, low energy consumption, low production cost, it has a number of potential applications in areas of earthquake relief, agricultural harvesting, medical facilities and space exploration.

This paper uses basic theory of material mechanics to deduct motion equations of the manipulator. Unlike other published papers, the manipulator is not based on segments tactics, but regarded as an integrated flexible system, which simplifies its kinematics modelling and motion controlling. The workspace of the manipulator is analysed by theoretical deducing and simulation modelling. For verification of the presented theory, simulation based on ADAMS software was implemented, while a prototype of the manipulator was developed. Both the software simulation and prototype experiment show that the theoretical analysis in this paper is reasonable. The manipulator can move accurately along the desired trajectories.

This paper developed a novel and fully continuous manipulator driven by steel wires. A kinematic model of the manipulator was established. The physical manipulator developed for verifying the kinematic model can effectively track the prescribed trajectory. The presented kinematic model agrees with not only the simulation but also with the experiment.

The manipulator presented in this paper is constructed by steel wires. It possesses the advantages of structural continuity, high flexibility and low production cost. It can be extensively used in many fields, such as search and rescue robotic systems. The limitation of this research is that the dynamic model of the manipulator is not yet clear, which is one of the directions for future research.

The manipulator breaks through the limitation of the joint-type or flexible-link-type manipulator, which can also be extensively used in many fields such as search and rescue robotic systems.

The manipulator developed in this paper, currently, is a prototype under the project of “Automatic Picking Manipulator Research”. It possesses a good market value.

The value of this research is that the manipulator breaks through the limitation of the joint-type or flexible-link-type manipulator and establishes the kinematic model for a fully continuous manipulator by a simple strategy. This is the first study that uses such a strategy for establishing the motion equations of a monolithic continuum manipulator.

In the industry, there is always a demand to shorten the task completion durations to maximize the efficiency of the operation. This work focuses on making use of a special type of kinematic redundancy, macro–micro manipulation, to minimize the task completion duration. The purpose of this paper is to develop the most convenient trajectory planner to be integrated with industrial computerized numerical control (CNC) systems to resolve kinematic redundancy for task duration minimization.

A special type of kinematic redundancy is devised by using two kinematically different mechanisms that have different advantages, which are named as macro and micro mechanisms. In this case, the control design including the trajectory planning should be devised taking into account the distinct advantages of both mechanisms. A new trajectory planning algorithm is designed and used for the constructed planar laser-cutting machine, and some benchmark pieces are cut.

Offline method has practical limitations for employment in a real case scenario such as assuming infinite jerk limits for each axis motion. This limitation was removed by using an online trajectory generation technique. Experimental test results indicate that the online trajectory planning technique developed for the macro–micro mechanism to shorten the task duration was successful.

Although the new trajectory planning algorithm is implemented for a laser-cutting machine, it can also be used for other manufacturing systems that require higher acceleration and accuracy levels than the conventional machines. The new algorithm is compatible with the commercially available CNC systems.

In this work, a new approach to reducing the task duration for planar machining operations was introduced by making use of macro–micro manipulation concept. The core novelty of the work is devising trajectory planning algorithms to get the most efficiency in terms of acceleration limits from a macro–micro manipulation while making these algorithms deployable to most of the CNC systems.