Results 61-80 of 96.
Bookmark and Share    
Full Text
Peer Reviewed
See detailAdaptive sliding mode fuzzy control for unknown robots with arbitrarily-switched constraints
Jasim, Ibrahim UL; Plapper, Peter UL; Voos, Holger UL

in Mechatronics (2015), 30C

This article addresses the control problem of robots with unknown dynamics and arbitrarily-switched unknown constraints. Such kind of robots will be shown to be unknown hybrid systems with arbitrary ... [more ▼]

This article addresses the control problem of robots with unknown dynamics and arbitrarily-switched unknown constraints. Such kind of robots will be shown to be unknown hybrid systems with arbitrary switching and an Adaptive Sliding Mode Fuzzy Control (ASMFC) strategy is proposed that handles the unknown dynamics of the robot along with the unknown constraints arbitrary switching. The ASMFC is a synergy of finding a Common Lyapunov Function (CLF) between the resulted switched subsystems of the considered robots, employing the Fuzzy Logic Systems (FLS), and the use of the Sliding Mode Control (SMC). The CLF accommodates the constraints arbitrary switching, the SMC adds robustness against possible parameters drift, and the FLS approximates the unknown robot dynamics. All unknown parameters are adapted online and all closed loop signals are guaranteed to be bounded. The proposed strategy is validated by conducting an experiment on a KUKA Lightweight Robot (LWR) doing a typical force-guided peg-in-hole assembly task that falls in the category of robot systems under consideration. Excellent tracking performance is obtained when using the ASMFC strategy. Comparison is conducted with the performance of a PD controller that is widely used in commanding industrial robots and the superiority of the proposed strategy is shown. [less ▲]

Detailed reference viewed: 121 (15 UL)
Full Text
Peer Reviewed
See detailContact-State Modelling in Force-Controlled Robotic Peg-in-Hole Assembly Processes of Flexible Objects Using Optimised Gaussian Mixtures
Jasim, Ibrahim UL; Plapper, Peter UL; Voos, Holger UL

in Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture (2015)

This article proposes the distribution similarity measure–based Gaussian mixtures model for the contact-state (CS) modelling in force-guided robotic assembly processes of flexible rubber parts. The wrench ... [more ▼]

This article proposes the distribution similarity measure–based Gaussian mixtures model for the contact-state (CS) modelling in force-guided robotic assembly processes of flexible rubber parts. The wrench (Cartesian force and torque) signals of the manipulated object are captured for different states of the given assembly process. The distribution similarity measure–based Gaussian mixtures model CS modelling scheme is employed in modelling the captured wrench signals for different CSs. The proposed distribution similarity measure–based Gaussian mixtures model CS modelling scheme uses the Gaussian mixtures model in modelling the captured signals. The parameters of the Gaussian mixtures models are computed using expectation maximisation. The optimal number of Gaussian mixtures model components for each CS model is determined by considering the classification success rate as an index for the similarity measure between the distribution of the captured signals and the developed models. The optimal number of Gaussian mixtures model components corresponds to the highest classification success rate; hence, object elasticity variation would be accommodated by properly choosing the optimal number of Gaussian mixtures model components. The performance of the proposed distribution similarity measure–based Gaussian mixtures model CS modelling strategy is evaluated by a test stand composed of a KUKA lightweight robot doing peg-in-hole assembly processes for flexible rubber objects. Two rubber objects with different elasticity are considered for two experiments; in the first experiment, an elastic peg of 30 Shore A hardness is considered and that of the second experiment has hardness of 6 Shore A which is even softer than the one used in experiment 1. Employing the proposed distribution similarity measure–based Gaussian mixtures model CS modelling strategy excellent classification success rate was obtained for both experiments. However, more Gaussian mixtures model components are required for the softer one that gives a strong impression of the non-stationarity behaviour increment for softer materials. Comparison is performed with the available CS modelling schemes and the distribution similarity measure–based Gaussian mixtures model is shown to provide the best classification success rate performance with a reduced computational time. [less ▲]

Detailed reference viewed: 90 (7 UL)
Full Text
Peer Reviewed
See detailAnt-Air self-learning algorithm for path planning in a cluttered environment
Ahmad, Rafiq UL; Plapper, Peter UL

in Applied Mechanics and Materials Journal (2014, December)

Path planning in unstructured area while dealing with narrow spaces is an area of research which is receiving extensive interest. Many existing algorithms are able to produce safe paths but the presented ... [more ▼]

Path planning in unstructured area while dealing with narrow spaces is an area of research which is receiving extensive interest. Many existing algorithms are able to produce safe paths but the presented concepts are either not adapted to narrow spaces or they are unable to learn from the past experience to improve repeated movements from the same agent or followed trajectories by other agents. This paper introduces an original concept based on Ant-Air phenomenon for safe path planning in a cluttered environment where narrow passages are treated. The algorithm presented is able to learn from the past experience and hence improve the already generated trajectory further by using some lessons learned from the past experience. The concept is applicable in various domains such as mobile robot path planning, manipulator trajectory generation and part movement in narrow passages in real or virtual assembly/disassembly process. [less ▲]

Detailed reference viewed: 109 (16 UL)
Full Text
Peer Reviewed
See detailHuman-Robot Collaboration: Twofold strategy algorithm to avoid collisions using ToF sensor
Ahmad, Rafiq UL; Plapper, Peter UL

in Applied Mechanics and Materials Journal (2014, December)

The importance of Human Robot Interaction to complement human skills in a manufacturing environment with industrial robots increases the concerns over safety of human and the robot. It is necessary to ... [more ▼]

The importance of Human Robot Interaction to complement human skills in a manufacturing environment with industrial robots increases the concerns over safety of human and the robot. It is necessary to identify collision risks and avoid them otherwise production stops may cost a huge amount to the industry. A robot working at manufacturing facility should be able to predict potential collisions and must be able to prevent i.e. react automatically for safe detour around obstacle/human. Currently, industrial robots are able to detect collisions after a real contact but the existing proposals for avoiding collisions are either computationally expensive or not very well adapted to human safety. The objective of this paper is to provide intelligence to the industrial robot to predict collision risks and react automatically without stopping the production in a static environment. The proposed approach using Time of Flight (TOF) camera, provides decision regarding trajectory correction and improvement by shifting robot to a secure position. The application presented in this paper is for safe KUKA robot trajectory generation in peg-in-hole assembly process in the laboratory context. [less ▲]

Detailed reference viewed: 158 (11 UL)
Full Text
Peer Reviewed
See detailSafe and Automated Tool-Path Generation for Multi-Axis Production Machines
Ahmad, Rafiq UL; Plapper, Peter UL

in Transactions of the American Society of Mechanical Engineers (2014, November 14), 2B(Advanced Manufacturing), 0202034-7

Multi-axis machines are growing rapidly their precision and complexity with the increasing importance of machine intelligence, automation, optimization and safety. It is necessary to identify collision ... [more ▼]

Multi-axis machines are growing rapidly their precision and complexity with the increasing importance of machine intelligence, automation, optimization and safety. It is necessary to identify collision risks and avoid them in manufacturing otherwise production stops may cost a huge amount to the manufacturing company. This study has focused on safe trajectory generation for CNC machines especially focusing on high risked non-functional trajectories. These machines should be able to see any unwilling situation (i.e. collisions) in their vicinity and must be able to detect and react automatically in real-time for safe tool movements. Currently CAM software and some multi-axis machines are able to detect collisions but they do not have any solution to avoid such collisions automatically. The main objective is to make multi-axis machine vision system effective enough that it can see all its activities regarding collisions and can react or command automatically online as well as off-line for real and virtual productions. In presence of obstacles during manufacturing, the proposed approach will provide decisions regarding trajectory correction and improvement automatically. The proposed vision concept is able to take into account the evolution of the scene i.e. the aspects of changes to the obstacle like shape, size or presence during production. The application presented in this paper is for 2D traversal safe online trajectories generation in virtual simulated dynamic environment, which will be adapted to the real-time real machining scenarios at shop-floor by integrating it with STEP-NC technology in future. [less ▲]

Detailed reference viewed: 80 (12 UL)
Full Text
Peer Reviewed
See detailPosition Identification in Force-Guided Robotic Peg-in-Hole Assembly Tasks
Jasim, Ibrahim UL; Plapper, Peter UL; Voos, Holger UL

in Procedia CIRP (2014), 22

Position uncertainty is inevitable in many force-guided robotic assembly tasks. Such uncertainty can cause a significant delay, extra energy expenditure, and may even results in detriments to the mated ... [more ▼]

Position uncertainty is inevitable in many force-guided robotic assembly tasks. Such uncertainty can cause a significant delay, extra energy expenditure, and may even results in detriments to the mated parts or the robot itself. This article suggests a strategy for identifying the accurate hole position in force-guided robotic peg-in-hole assembly tasks through employing only the captured wrench (the Cartesian forces and torques) signals of the manipulated. In the framework of using the Contact-State (CS) modeling for such robotic tasks, the identification of the hole position is realized through detecting the CS that corresponds for the phase of the peg-on-hole, that is the phase in which the peg is located precisely on the hole. Expectation Maximization-based Gaussian Mixtures Model (EM-GMM) CS modeling scheme is employed in detecting the CS corresponding for the peg-on-hole phase. Only the wrench signals are used in modeling and detecting the phases of the assembly process. The considered peg-in-hole assembly process starts from free space and as soon as the peg touches the environment with missing the hole, a spiral search path is followed that would survey the whole environment surface. When the CS of the peg-on-hole is detected, the hole position is identified. Experiments are conducted on a KUKA Lightweight Robot (LWR) doing typical peg-in-hole assembly tasks. Multiple hole positions are considered and excellent performance of the proposed identification strategy is shown. [less ▲]

Detailed reference viewed: 74 (16 UL)
Full Text
Peer Reviewed
See detailEnhanced Decentralized Robust Adaptive Control of Robots With Arbitrarily-Switched Unknown Constraints
Jasim, Ibrahim UL; Plapper, Peter UL

in 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC2014) (2014, October 05)

In this article, we propose an Enhanced Decentralized Robust Adaptive Control (EDRAC) strategy that guarantees global stable performance for robots under arbitrarily-switched and unknown constraints. The ... [more ▼]

In this article, we propose an Enhanced Decentralized Robust Adaptive Control (EDRAC) strategy that guarantees global stable performance for robots under arbitrarily-switched and unknown constraints. The EDRAC strategy is a synergy of the concepts of the decentralized control, finding a Common Lyapunov Function (CLF), and the Sliding Mode Control (SMC). The decentralization in the control action is realized through decomposing the joints dynamics into two parts; a function of the specific joint variables and another one in term of the all joints variables. The first term is assumed to be known and the latter is compensated through adapting its upper bound in the control loop hence relaxing the need for knowing part of the robot dynamics and simplifying the control strategy. The CLF guarantees global stable performance under arbitrary constraints switching, and the SMC makes the EDRAC strategy robust against possible parameters drift. Simulation is performed for a two link robot interacting with two switching constraints and the efficiency of the EDRAC strategy is shown. [less ▲]

Detailed reference viewed: 44 (10 UL)
Full Text
Peer Reviewed
See detail2D Tool-Path Generation Method for Multi-Axis Milling Machine using ToF camera
Ahmad, Rafiq UL; Plapper, Peter UL

Scientific Conference (2014, September 12)

Multi-axis machines are known for their precise production of complex parts, where multi-tool are working in the same area or static workpiece support or clamping parts, may cause collision problems. It ... [more ▼]

Multi-axis machines are known for their precise production of complex parts, where multi-tool are working in the same area or static workpiece support or clamping parts, may cause collision problems. It is therefore necessary to identify potential collision risks and avoid them in an efficient way, which may cause production stops and machinery damage. This research study has been focusing on safe non-functional (rapid) tool-path generation for multi-axis milling machine, where no efficient automatic collision avoidance solution exists (in the literature). A 3D Time of Flight (TOF) camera attached into the machine will be able to sense any unwanted situation in the manufacturing environment and provide rapid and automatic solution to detect and avoid collisions for safe tool movements during production. In the presence of obstacles, the proposed approach will provide decisions regarding tool-path correction and improvement automatically. The proposed algorithm based on 3D vision concept is also able to take into account unknown obstacle shape, size during production but dynamic aspects of the scene will be treated in future. The concept presented take into account the 3D information from the scene for traversal safe tool-paths generation for a static environment as an initial application, which will be adapted to more complex real machining scenarios by integrating it with STEP-NC technology in future. [less ▲]

Detailed reference viewed: 120 (6 UL)
Full Text
Peer Reviewed
See detailRobust Direct Adaptive Fuzzy Control of Switched Constrained Manipulators with Unknown Dynamics
Jasim, Ibrahim UL; Plapper, Peter UL

in Joint 45th International Symposium on Robotics (ISR 2014) and 8th German Conference on Robotics (ROBOTIK 2014) (2014, June 02)

In this article, we address the problem of controlling robots with arbitrarily-switched constraints and unknown dynamics. Switching between different constraints of a robot would result in a switched ... [more ▼]

In this article, we address the problem of controlling robots with arbitrarily-switched constraints and unknown dynamics. Switching between different constraints of a robot would result in a switched nonlinear system that does not inherit the behavior of its individual subsystems. In order to guarantee stable performance of robots with arbitrarily switched constraints and unknown dynamics, we propose a Robust Adaptive Fuzzy Control (RAFC) strategy that can guarantee global stable performance under such challenging conditions. The suggested control strategy relies on the synergy of the Sliding Mode Control (SMC) that adds robustness against possible dynamics parameters drift, finding a Common Lyapunov Function (CLF) that guarantees stability under arbitrary constraints switching, and Direct Adaptive Fuzzy System (DAFS) that relaxes the need for knowing the precise robot dynamics. Experiments are performed on a KUKA Lightweight Robot (LWR) doing camshaft caps assembly of an automotive powertrain. The given robotic assembly process falls in the category of switched constrained robots and the efficiency of the suggested RAFC strategy in controlling such a robotic task will be shown. [less ▲]

Detailed reference viewed: 50 (6 UL)
Full Text
Peer Reviewed
See detailRobust Direct Adaptive Fuzzy Control of Flexible Joints Robots with Time-Varying Stiffness/Damping Parameters
Jasim, Ibrahim UL; Plapper, Peter UL

in Joint 45th International Symposium on Robotics (ISR 2014) and 8th German Conference on Robotics (ROBOTIK 2014) (2014, June 02)

In this article, we address the problem of controlling unknown flexible-joint robots with unknown time-varying stiffness and damping parameters. We propose a Robust Direct Adaptive Fuzzy Control (RDAFC ... [more ▼]

In this article, we address the problem of controlling unknown flexible-joint robots with unknown time-varying stiffness and damping parameters. We propose a Robust Direct Adaptive Fuzzy Control (RDAFC) strategy that accommodates the dynamics anonymity and joints stiffness/damping variations. The RDAFC strategy relies on the synergy of the concepts of fuzzy logic approximation and the Sliding Mode Control (SMC). The fuzzy logic approximation relaxes the need for knowing the robot dynamics and the SMC accommodates the parameters variations. We also modify the RDAFC strategy to be suited to the KUKA Lightweight Robot (LWR) and propose a control strategy that can accommodates dynamics anonymity, uncertainty and joints elasticity variations. Experimental results are performed on a KUKA LWR moving in free space with its joints stiffness and damping vary with time in sine and cosine waveforms respectively. From the experiments, we can see that excellent tracking performance is obtained when using the RDAFC strategy despite the joints elasticity parameters time-variance and the robot dynamics unavailability. [less ▲]

Detailed reference viewed: 47 (6 UL)
Full Text
Peer Reviewed
See detailContact-State Recognition of Compliant Motion Robots Using Expectation Maximization-Based Gaussian Mixtures
Jasim, Ibrahim UL; Plapper, Peter UL

in Joint 45th International Symposium on Robotics (ISR 2014) and 8th German Conference on Robotics (ROBOTIK 2014) (2014, June 02)

In this article, we address the problem of Contact-State (CS) recognition for force-controlled robotic tasks. At first, the wrench (Cartesian forces and torques) and pose (Cartesian position and ... [more ▼]

In this article, we address the problem of Contact-State (CS) recognition for force-controlled robotic tasks. At first, the wrench (Cartesian forces and torques) and pose (Cartesian position and orientation) signals of the manipulated object, in different Contact Formations (CFs) of a task, are collected. Then in the framework of the Bayesian classification, the Expectation Maximization-based Gaussian Mixtures Model (EM-GMM) is used in building efficient CFs classifiers. The use of the EM-GMM in developing the captured signals models accommodates possible signals non-stationarity, i.e. signals abnormal distribution, and enhanced recognition performance would be resulted. Experiments are performed on a KUKA Lightweight Robot (LWR) doing the cube-in-corner assembly task, which is a rigid cube object interacting with an environment composed of three orthogonal planes, and different CFs are considered. From the experimental results, the EM-GMM is shown to have an excellent recognition performance with an enhanced computational time. In order to compare the EM-GMM with the available CF recognition schemes, we developed the corresponding CF classifiers using the Gravitational Search-Fuzzy Clustering Algorithm (GS-FCA), Stochastic Gradient Boosting (SGB), and the Conventional Fuzzy Classifier(CFC) approaches. From the comparison results it is obvious that the EM-GMM scheme is outperforming the rest. [less ▲]

Detailed reference viewed: 120 (4 UL)
Full Text
Peer Reviewed
See detailElectrical performance of laser braze-welded aluminum–copper interconnects
Solchenbach, Tobias UL; Plapper, Peter UL; Cai, Wayne

in Journal of Manufacturing Processes (2014), 16(2), 183-189

Detailed reference viewed: 75 (5 UL)
Full Text
Peer Reviewed
See detailLaser Assisted Joining of Hybrid Polyamide-aluminum Structures
Lamberti, Christian UL; Solchenbach, Tobias UL; Plapper, Peter UL et al

in Physics Procedia (2014), 56(0), 845-853

Detailed reference viewed: 152 (20 UL)
Full Text
Peer Reviewed
See detailContact-state modeling of robotic assembly tasks using Gaussian mixture models
Ibrahim, Jasim; Plapper, Peter UL

in Procedia CIRP (2014), 23

This article addresses the Contact-State (CS) modeling problem for the force-controlled robotic peg-in-hole assembly tasks. The wrench (Cartesian forces and torques) and pose (Cartesian position and ... [more ▼]

This article addresses the Contact-State (CS) modeling problem for the force-controlled robotic peg-in-hole assembly tasks. The wrench (Cartesian forces and torques) and pose (Cartesian position and orientation) signals, of the manipulated object, are captured for different phases of the robotic assembly task. Those signals are utilized in building a CS model for each phase. Gaussian Mixture Models (GMM) is employed in building the likelihood of each signal and Expectation Maximization (EM) is used in finding the GMM parameters. Experiments are performed on a KUKA Lightweight Robot (LWR) doing camshaft caps assembly of an automotive powertrain. Comparisons are also performed with the available assembly modeling schemes, and the superiority of the EM-GMM scheme is shown with a reduced computational time. [less ▲]

Detailed reference viewed: 63 (1 UL)
Full Text
Peer Reviewed
See detailContact-state modeling of robotic assembly tasks using Gaussian mixture models
Jasim, Ibrahim UL; Plapper, Peter UL

in Procedia CIRP (2014), 23

This article addresses the Contact-State (CS) modeling problem for the force-controlled robotic peg-in-hole assembly tasks. The wrench (Cartesian forces and torques) and pose (Cartesian position and ... [more ▼]

This article addresses the Contact-State (CS) modeling problem for the force-controlled robotic peg-in-hole assembly tasks. The wrench (Cartesian forces and torques) and pose (Cartesian position and orientation) signals, of the manipulated object, are captured for different phases of the robotic assembly task. Those signals are utilized in building a CS model for each phase. Gaussian Mixture Models (GMM) is employed in building the likelihood of each signal and Expectation Maximization (EM) is used in finding the GMM parameters. Experiments are performed on a KUKA Lightweight Robot (LWR) doing camshaft caps assembly of an automotive powertrain. Comparisons are also performed with the available assembly modeling schemes, and the superiority of the EM-GMM scheme is shown with a reduced computational time. [less ▲]

Detailed reference viewed: 59 (5 UL)
Full Text
Peer Reviewed
See detailPosition identification in force-guided peg-in-hole assembly tasks
Ibrahim, Jasim; Plapper, Peter UL; Voos, Holger UL

in Procedia CIRP (2014), 23

Position uncertainty is inevitable in many force-guided robotic assembly tasks. Such uncertainty can cause a significant delay, extra energy expenditure, and may even results in detriments to the mated ... [more ▼]

Position uncertainty is inevitable in many force-guided robotic assembly tasks. Such uncertainty can cause a significant delay, extra energy expenditure, and may even results in detriments to the mated parts or the robot itself. This article suggests a strategy for identifying the accurate hole position in force-guided robotic peg-in-hole assembly tasks through employing only the captured wrench (the Cartesian forces and torques) signals of the manipulated. In the framework of using the Contact-State (CS) modeling for such robotic tasks, the identification of the hole position is realized through detecting the CS that corresponds for the phase of the peg-on-hole, that is the phase in which the peg is located precisely on the hole. Expectation Maximization-based Gaussian Mixtures Model (EM-GMM) CS modeling scheme is employed in detecting the CS corresponding for the peg-on-hole phase. Only the wrench signals are used in modeling and detecting the phases of the assembly process. The considered peg-in-hole assembly process starts from free space and as soon as the peg touches the environment with missing the hole, a spiral search path is followed that would survey the whole environment surface. When the CS of the peg-on-hole is detected, the hole position is identified. Experiments are conducted on a KUKA Lightweight Robot (LWR) doing typical peg-in-hole assembly tasks. Multiple hole positions are considered and excellent performance of the proposed identification strategy is shown. [less ▲]

Detailed reference viewed: 29 (0 UL)
Full Text
Peer Reviewed
See detailThermal and electrical aging of laser braze-welded aluminum–copper interconnects
Solchenbach, Tobias UL; Plapper, Peter UL; Greger, Manfred UL et al

in Translational Materials Research (2014), 1(1), 015001

Aluminum–copper (Al–Cu) interconnects are of great interest for a variety of electrical applications, such as lithium-ion batteries. In this paper, the effects of thermal and electrical aging on the ... [more ▼]

Aluminum–copper (Al–Cu) interconnects are of great interest for a variety of electrical applications, such as lithium-ion batteries. In this paper, the effects of thermal and electrical aging on the intermetallic compound growth of laser braze-welded Al–Cu interconnects are reported. Thermal aging was studied in a temperature range from 200 to 500 °C for durations between 1 and 120 h. Electrical aging was studied with 200 A direct current application with different polarities and durations between 1 and 24 h. The formation of intermetallic compounds was found to be dependent on the type of aging and, for electrical aging, on the polarity of the current. The growth of intermetallic compounds under the influence of the electric current was distinctly higher than for thermal annealing conditions. The formation of voids at the transition between intermetallic compounds indicates that electromigration may be the main driving force for the accelerated intermetallic growth. [less ▲]

Detailed reference viewed: 81 (11 UL)
Full Text
Peer Reviewed
See detailContact-State Monitoring of Force-Guided Robotic Assembly Tasks Using Expectation Maximization-based Gaussian Mixtures Models
Jasim, Ibrahim UL; Plapper, Peter UL

in International Journal of Advanced Manufacturing Technology (2014), 73(5), 623-633

This article addresses the problem of Contact-State (CS) monitoring for peg-in-hole force-controlled robotic assembly tasks. In order to perform such a monitoring target, the wrench (Cartesian forces and ... [more ▼]

This article addresses the problem of Contact-State (CS) monitoring for peg-in-hole force-controlled robotic assembly tasks. In order to perform such a monitoring target, the wrench (Cartesian forces and torques) and pose (Cartesian position and orientation) signals of the manipulated object are firstly captured for different CS's of the object (peg) with respect to the environment including the hole. The captured signals are employed in building a model (a recognizer) for each CS and in the framework of pattern classification the CS monitoring would be addressed. It will be shown that the captured signals are non-stationary, i.e. they have non-normal distribution that would result in performance degradation if using the available monitoring approaches. In this article, the concept of the Gaussian Mixtures Models (GMM) is used in building the likelihood of each signal and the Expectation Maximization (EM) algorithm is employed in finding the GMM parameters. The use of the GMM would accommodate the signals non-stationary behavior and the EM algorithm would guarantee the estimation of the optimal parameters set of the GMM for each signal and hence the modeling accuracy would be significantly enhanced. In order to see the performance of the suggested CS monitoring scheme, we installed a test stand that is composed of a KUKA Lightweight Robot (LWR) doing a typical peg-in-hole tasks. Two experiments are considered; in the first experiment we use the EM-GMM in monitoring a typical peg-in-hole robotic assembly process and in the second experiment we consider the robotic assembly of camshaft caps assembly of an automotive powertrain and use the EM-GMM in monitoring its CS's. For both experiments, the excellent monitoring performance will be shown. Furthermore, we compare the performance of the EM-GMM with that obtained when using available CS monitoring approaches. Classification Success Rate (CSR) and computational time will be considered as comparison indices and the EM-GMM will be shown to have a superior CSR performance with reduced a computational time. [less ▲]

Detailed reference viewed: 130 (19 UL)
Full Text
Peer Reviewed
See detailStable Robust Adaptive Control of Robotic Manipulators with Switched Constraints
Jasim, Ibrahim UL; Plapper, Peter UL

in Proceedings of the 2013 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2013 (2013, August)

In this paper, the problem of controlling switched constrained robotic manipulators is addressed. Switched constrained robots are those robots interacting with multiple switched constraints. We start our ... [more ▼]

In this paper, the problem of controlling switched constrained robotic manipulators is addressed. Switched constrained robots are those robots interacting with multiple switched constraints. We start our control algorithm with suggesting a sliding mode controller that is proved to provide stable system performance. However, the bounds of the functions, on each link, caused from the constraints are assumed to be known. Then an adaptive sliding mode control strategy is suggested that relaxes the need for knowing the bounds of the constraints functions with guaranteeing global stable performance of the given switched constrained robotic system. Finally, we complement the control strategy above through deriving an improved robust adaptive control scheme that is proved to give a stable performance with reduced chattering. All of the three stages of the suggested control strategy are derived through finding a common Lyapunov function that can stabilize all of the subsystems for the overall switched system. Simulation is carried out for a two link robotic manipulator interacting with two switched constraints. From the simulation results we can see the excellent tracking performance and the high efficiency of the suggested control strategy in controlling switched constrained robotic systems. [less ▲]

Detailed reference viewed: 71 (21 UL)