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1 – 10 of over 2000Weilin Yang, Wentao Zhang, Dezhi Xu and Wenxu Yan
Robotic arm control is challenging due to the intrinsic nonlinearity. Proportional-integral-derivative (PID) controllers prevail in many robotic arm applications. However, it is…
Abstract
Purpose
Robotic arm control is challenging due to the intrinsic nonlinearity. Proportional-integral-derivative (PID) controllers prevail in many robotic arm applications. However, it is usually nontrivial to tune the parameters in a PID controller. This paper aims to propose a model-based control strategy of robotic arms.
Design/methodology/approach
A Takagi–Sugeno (T-S) fuzzy model, which is capable of approximating nonlinear systems, is used to describe the dynamics of a robotic arm. Model predictive control (MPC) based on the T-S fuzzy model is considered, which optimizes system performance with respect to a user-defined cost function.
Findings
The control gains are optimized online according to the real-time system state. Furthermore, the proposed method takes into account the input constraints. Simulations demonstrate the effectiveness of the fuzzy MPC approach. It is shown that asymptotic stability is achieved for the closed-loop control system.
Originality/value
The T-S fuzzy model is discussed in the modeling of robotic arm dynamics. Fuzzy MPC is used for robotic arm control, which can optimize the transient performance with respect to a user-defined criteria.
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The purpose of this paper is to reduce the strain and vibration during robotic machining.
Abstract
Purpose
The purpose of this paper is to reduce the strain and vibration during robotic machining.
Design/methodology/approach
An intelligent approach based on particle swarm optimization (PSO) and adaptive iteration algorithms is proposed to optimize the PD control parameters in accordance with robotic machining state.
Findings
The proposed intelligent approach can significantly reduce robotic machining strain and vibration.
Originality value
The relationship between robotic machining parameters is studied and the dynamics model of robotic machining is established. In view of the complexity of robotic machining process, the PSO and adaptive iteration algorithms are used to optimize the PD control parameters in accordance with robotic machining state. The PSO is used to optimize the PD control parameters during stable-machining state, and the adaptive iteration algorithm is used to optimize the PD control parameters during cut-into state.
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Fusheng Liu, Zhihang He, Yue Qiao, Xinxin Liu, Xuelong Li, Wang Wei, Bo Su and Ruina Dang
The purpose of this paper is specifically to provide a more intelligent locomotion planning method for a hexapod robot based on trajectory optimization, which could reduce the…
Abstract
Purpose
The purpose of this paper is specifically to provide a more intelligent locomotion planning method for a hexapod robot based on trajectory optimization, which could reduce the complexity of locomotion design, shorten time of design and generate efficient and accurate motion.
Design/methodology/approach
The authors generated locomotion for the hexapod robot based on trajectory optimization method and it just need to specify the high-level motion requirements. Here the authors first transcribed the trajectory optimization problem to a nonlinear programming problem, in which the specified motion requirements and the dynamics with complementarity constraints were defined as the constraints, then a nonlinear solver was used to solve. The leg compliance was taken into consideration and the generated motions were deployed on the hexapod robot prototype to prove the utility of the method and, meanwhile, the influence of different environments was considered.
Findings
The generated motions were deployed on the hexapod robot and the movements were demonstrated very much in line with the planning. The new planning method does not require lots of parameter-tuning work and therefore significantly reduces the cycle for designing a new locomotion.
Originality/value
A locomotion generation method based on trajectory optimization was constructed for a 12-degree of freedom hexapod robot. The variable stiffness compliance of legs was considered to improve the accuracy of locomotion generation. And also, different from some simulation work before, the authors have designed the locomotion in three cases and constructed field tests to demonstrate its utility.
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Ali Fazli and Mohammad Hosein Kazemi
This paper aims to propose a new linear parameter varying (LPV) controller for the robot tracking control problem. Using the identification of the robot dynamics in different work…
Abstract
Purpose
This paper aims to propose a new linear parameter varying (LPV) controller for the robot tracking control problem. Using the identification of the robot dynamics in different work space points about modeling trajectory based on the least square of error algorithm, an LPV model for the robotic arm is extracted.
Design/methodology/approach
Parameter set mapping based on parameter component analysis results in a reduced polytopic LPV model that reduces the complexity of the implementation. An approximation of the required torque is computed based on the reduced LPV models. The state-feedback gain of each zone is computed by solving some linear matrix inequalities (LMIs) to sufficiently decrease the time derivative of a Lyapunov function. A novel smoothing method is used for the proposed controller to switch properly in the borders of the zones.
Findings
The polytopic set of the resulting gains creates the smooth switching polytopic LPV (SS-LPV) controller which is applied to the trajectory tracking problem of the six-degree-of-freedom PUMA 560 robotic arm. A sufficient condition ensures that the proposed controller stabilizes the polytopic LPV system against the torque estimation error.
Practical implications
Smoothing of the switching LPV controller is performed by defining some tolerances and creating some quasi-zones in the borders of the main zones leading to the compressed main zones. The proposed torque estimation is not a model-based technique; so the model variation and other disturbances cannot destroy the performance of the suggested controller. The proposed control scheme does not have any considerable computational load, because the control gains are obtained offline by solving some LMIs, and the torque computation is done online by a simple polytopic-based equation.
Originality/value
In this paper, a new SS-LPV controller is addressed for the trajectory tracking problem of robotic arms. Robot workspace is zoned into some main zones in such a way that the number of models in each zone is almost equal. Data obtained from the modeling trajectory is used to design the state-feedback control gain.
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Khalil Alipour and S. Ali A. Moosavian
A suspended wheeled mobile robot (SWMR) that consists of one or more manipulators can be exploited in various environmental conditions such as uneven surfaces. The purpose of this…
Abstract
Purpose
A suspended wheeled mobile robot (SWMR) that consists of one or more manipulators can be exploited in various environmental conditions such as uneven surfaces. The purpose of this paper is to discuss the requirements for stable motion planning of such robotic systems to perform heavy object manipulation tasks.
Design/methodology/approach
First, a systematic procedure for dynamics modelling of such complicated systems for planar motion is presented and verified using ADAMS simulation software. Next, based on the new dynamic moment‐height stability (MHS) measure, the stability of such systems will be investigated using the obtained dynamics. To this end, introducing the concept of a virtual frame, the obtained model of SWMR has been employed for investigating the effect of the base suspension characteristics as well as terrain roughness on the stability of the system. Next, the stability evaluation of the system is investigated after toppling down which has been rarely addressed in the literature. In addition, using the aforementioned model, the effect of stiffness is examined after instability.
Findings
First, a systematic procedure for dynamics modelling of such complicated systems for planar motion is presented and verified using ADAMS simulation software. Next, based on the new dynamic MHS measure, the stability of such systems will be investigated using the obtained dynamics. To this end, introducing the concept of a virtual frame, the obtained model of SWMR has been employed for investigating the effect of the base suspension characteristics as well as terrain roughness on the stability of the system. Next, the stability evaluation of the system is investigated after toppling down which has been rarely addressed in the literature. In addition, using the aforementioned model, the effect of stiffness is examined after instability.
Originality/value
A general procedure for dynamics modelling of SWMRs is presented. To verify the obtained dynamics model, another model for the considered system has been developed by ADAMS software. Next, using the obtained dynamics, the postural stability of such systems is investigated, based on the new postural MHS measure extended for SWMRs. The obtained simulation results show that by decreasing the stiffness coefficients of suspension subsystem the stability of the system weakens.
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Jiajun Xu, Linsen Xu, Gaoxin Cheng, Jia Shi, Jinfu Liu, Xingcan Liang and Shengyao Fan
This paper aims to propose a bilateral robotic system for lower extremity hemiparesis rehabilitation. The hemiplegic patients can complete rehabilitation exercise voluntarily with…
Abstract
Purpose
This paper aims to propose a bilateral robotic system for lower extremity hemiparesis rehabilitation. The hemiplegic patients can complete rehabilitation exercise voluntarily with the assistance of the robot. The reinforcement learning is included in the robot control system, enhancing the muscle activation of the impaired limbs (ILs) efficiently with ensuring the patients’ safety.
Design/methodology/approach
A bilateral leader–follower robotic system is constructed for lower extremity hemiparesis rehabilitation, where the leader robot interacts with the healthy limb (HL) and the follow robot is worn by the IL. The therapeutic training is transferred from the HL to the IL with the assistance of the robot, and the IL follows the motion trajectory prescribed by the HL, which is called the mirror therapy. The model reference adaptive impedance control is used for the leader robot, and the reinforcement learning controller is designed for the follower robot. The reinforcement learning aims to increase the muscle activation of the IL and ensure that its motion can be mastered by the HL for safety. An asynchronous algorithm is designed by improving experience relay to run in parallel on multiple robotic platforms to reduce learning time.
Findings
Through clinical tests, the lower extremity hemiplegic patients can rehabilitate with high efficiency using the robotic system. Also, the proposed scheme outperforms other state-of-the-art methods in tracking performance, muscle activation, learning efficiency and rehabilitation efficacy.
Originality/value
Using the aimed robotic system, the lower extremity hemiplegic patients with different movement abilities can obtain better rehabilitation efficacy.
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John Ogbemhe and Khumbulani Mpofu
– The purpose of this paper is to review the progress made in arc welding automation using trajectory planning, seam tracking and control methodologies.
Abstract
Purpose
The purpose of this paper is to review the progress made in arc welding automation using trajectory planning, seam tracking and control methodologies.
Design/methodology/approach
This paper discusses key issues in trajectory planning towards achieving full automation of arc welding robots. The identified issues in trajectory planning are real-time control, optimization methods, seam tracking and control methodologies. Recent research is considered and brief conclusions are drawn.
Findings
The major difficulty towards realizing a fully intelligent robotic arc welding system remains an optimal blend and good understanding of trajectory planning, seam tracking and advanced control methodologies. An intelligent trajectory tracking ability is strongly required in robotic arc welding, due to the positional errors caused by several disturbances that prevent the development of quality welds. An exciting prospect will be the creation of an effective hybrid optimization technique which is expected to lead to new scientific knowledge by combining robotic systems with artificial intelligence.
Originality/value
This paper illustrates the vital role played by optimization methods for trajectory design in arc robotic welding automation, especially the non-gradient approaches (those based on certain characteristics and behaviour of biological, molecular, swarm of insects and neurobiological systems). Effective trajectory planning techniques leading to real-time control and sensing systems leading to seam tracking have also been studied.
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Feifei Zhong, Guoping Liu, Zhenyu Lu, Lingyan Hu, Yangyang Han, Yusong Xiao and Xinrui Zhang
Robotic arms’ interactions with the external environment are growing more intricate, demanding higher control precision. This study aims to enhance control precision by…
Abstract
Purpose
Robotic arms’ interactions with the external environment are growing more intricate, demanding higher control precision. This study aims to enhance control precision by establishing a dynamic model through the identification of the dynamic parameters of a self-designed robotic arm.
Design/methodology/approach
This study proposes an improved particle swarm optimization (IPSO) method for parameter identification, which comprehensively improves particle initialization diversity, dynamic adjustment of inertia weight, dynamic adjustment of local and global learning factors and global search capabilities. To reduce the number of particles and improve identification accuracy, a step-by-step dynamic parameter identification method was also proposed. Simultaneously, to fully unleash the dynamic characteristics of a robotic arm, and satisfy boundary conditions, a combination of high-order differentiable natural exponential functions and traditional Fourier series is used to develop an excitation trajectory. Finally, an arbitrary verification trajectory was planned using the IPSO to verify the accuracy of the dynamical parameter identification.
Findings
Experiments conducted on a self-designed robotic arm validate the proposed parameter identification method. By comparing it with IPSO1, IPSO2, IPSOd and least-square algorithms using the criteria of torque error and root mean square for each joint, the superiority of the IPSO algorithm in parameter identification becomes evident. In this case, the dynamic parameter results of each link are significantly improved.
Originality/value
A new parameter identification model was proposed and validated. Based on the experimental results, the stability of the identification results was improved, providing more accurate parameter identification for further applications.
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Keywords
A. Miller, P. Allen, V. Santos and F. Valero‐Cuevas
Robotic hands are still a long way from matching the grasping and manipulation capability of their human counterparts, but computer simulation may help us understand this…
Abstract
Purpose
Robotic hands are still a long way from matching the grasping and manipulation capability of their human counterparts, but computer simulation may help us understand this disparity. We present our publicly available simulator, and describe our research projects involving the system including the development of a human hand model derived from experimental measurements.
Design/methodology/approach
Unlike other simulation systems, our system was built specifically to analyze grasps. It can import a wide variety of robot designs by using standard descriptions of the kinematics and link geometries. Various components support the analysis of grasps, visualization of results, dynamic simulation of grasping tasks, and grasp planning.
Findings
The simulator has been used in several grasping research problems and can be used to plan grasps for an actual robot. With the aid of a vision system, we have shown that these grasps can be executed by a robot.
Research limitations/implications
We are currently developing methods to handle deformable surfaces, tendon driven models, and non‐ideal joints in order to better model human grasping.
Practical implications
This work is part of our current project to create a biomechanically realistic human hand model to better understand what features are most important to mimic in the designs of robotic hands. Such a model will also help clinicians better plan reconstructive hand surgeries.
Originality/value
We describe our publicly available grasping simulator and review experiments performed with it. The paper demonstrates the usefulness of this system as a tool for grasping research.
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Li Pan, Guanjun Bao, Fang Xu and Libin Zhang
This paper aims to present an adaptive robust sliding mode tracking controller for a 6 degree-of-freedom industrial assembly robot with parametric uncertainties and external…
Abstract
Purpose
This paper aims to present an adaptive robust sliding mode tracking controller for a 6 degree-of-freedom industrial assembly robot with parametric uncertainties and external disturbances. The controller is used to achieve both stringent trajectory tracking, accurate parameter estimations and robustness against external disturbances.
Design/methodology/approach
The controller is designed based on the combination of sliding mode control, adaptive and robust controls and hence has good adaptation and robustness abilities to parametric variations and uncertainties. The unknown parameter estimates are updated online based on a discontinuous projection adaptation law. The robotic dynamics is first formulated in both joint spaces and workspace of the robot’s end-effector. Then, the design procedure of the adaptive robust sliding mode tracking controller and the parameter update law is detailed.
Findings
Comparative tests are also conducted to verify the effectiveness of the proposed controller, which show that the proposed controller achieves significantly better dynamic trajectory tracking performances as compared with conventional proportional derivative controller and sliding mode controller under the same conditions.
Originality/value
This is a new innovation for industrial assembly robot to improve assembly automation.
Details