Enhanced Decentralized Robust Adaptive Control of Robots With Arbitrarily-Switched Unknown Constraints

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 ▲]

2D Tool-Path Generation Method for Multi-Axis Milling Machine using ToF camera

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 ▲]

Robust Direct Adaptive Fuzzy Control of Flexible Joints Robots with Time-Varying Stiffness/Damping Parameters

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 ▲]

Electrical performance of laser braze-welded aluminum–copper interconnects

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

Contact-state modeling of robotic assembly tasks using Gaussian mixture models

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 ▲]

Position identification in force-guided peg-in-hole assembly tasks

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 ▲]

Contact-State Monitoring of Force-Guided Robotic Assembly Tasks Using Expectation Maximization-based Gaussian Mixtures Models

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 ▲]

Adaptive Sliding Mode Control of Switched Constrained Robotic Manipulators

in 2013 IEEE International Conference on Industrial Informatics, Bochum 28-30 July 2013 (2013, July)

In this paper, we address the control problem of a constrained robotic manipulators with their constraints continuously switched from one to another. Such a switching in the constraints causes a switching ... [more ▼]

In this paper, we address the control problem of a constrained robotic manipulators with their constraints continuously switched from one to another. Such a switching in the constraints causes a switching function to be inserted in the equation of the robot dynamics which may cause transient instability for the overall system. Two robust control strategies are presented in this paper to handle such switched robotic systems. In the first strategy, we assume that the bounds of the constraints are known. A sliding mode stabilizing controller is developed that can guarantee global stable performance of the given robotic system. In the second one, we relax the assumption of knowing the constraints bounds through deriving update laws for those bounds and new control actions that can guarantee global stable performance under such switching constraints. Simulation is performed for a two link robotic system having two switching constraints. The results obtained from the simulation verify the efficacy of the suggested control strategy. [less ▲]

T-S Fuzzy Contact State Recognition for Compliant Motion Robotic Tasks Using Gravitational Search-Based Clustering Algorithm

in 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2013) (2013, July)

In this paper, we address the problem of contact state recognition for compliant motion robotic systems. The wrench (Cartesian forces and torques) and pose (position and orientation) of the manipulated ... [more ▼]

In this paper, we address the problem of contact state recognition for compliant motion robotic systems. The wrench (Cartesian forces and torques) and pose (position and orientation) of the manipulated object in different Contact Formations (CFs) are firstly captured during a certain task execution. Then for each CF, we develop an efficient Takagi- Sugeno (T-S) fuzzy inference system that can model that specific CF using the available input (wrench and pose) - output (the desired model output for each CF) data. The antecedent part parameters are computed using the Gravitational Search- based Fuzzy Clustering Algorithm (GS- FCA) and the consequent parts parameters are tuned by the Least Mean Square (LMS). Excellent mapping and hence recognition capabilities can be expected from the suggested scheme. In order to validate the approach; experimental test stand is built which is composed of a KUKA Light Weight Robot (LWR) manipulating a cube rigid object that interacts with an environment composed of three orthogonal planes. The manipulated object is rigidly attached to the robot arm. The robot is programmed, by a human operator, to move in different CFs and for each CF, the wrench and pose readings are captured via the Fast Research Interface (FRI) available at the KUKA LWR. Using the suggested approach, excellent modeling is obtained for different CFs during the robot task execution. A comparison with the available CF recognition approaches is also performed and the superiority of the suggested scheme is shown. [less ▲]

Combined Laser Beam Braze-Welding Process for Fluxless Al-Cu Connections

in Dimitrov, Dimiter; Schutte, Corne (Eds.) PROCEDINGS International Conference on competitive Manufacturing, COMA 13 (2013, January)

A combined laser beam welding and brazing process for Al-Cu connections in overlap configuration is investigated. Aluminium and copper for electric and electronic application is used for experiments ... [more ▼]

A combined laser beam welding and brazing process for Al-Cu connections in overlap configuration is investigated. Aluminium and copper for electric and electronic application is used for experiments without surface treatment or activation, e.g. by flux. Although Al and Cu have been considered as “not weldable”, the possibility of a thermal joining process, i.e., the weld-brazing, was proved. The inevitable formation of intermetallic compounds at the interfacial region was reduced to less than 4 µm. Shear strength up to 51 MPa was achieved. A detailed fracture analysis has shown that the copper-rich intermetallic phase is the metallurgical weakest point due to the distinctive brittleness, even though the Al-rich Cu-phase is several times thicker. [less ▲]