1,932 research outputs found

    Improving Dynamics Estimations and Low Level Torque Control Through Inertial Sensing

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    In 1996, professors J. Edward Colgate and Michael Peshkin invented the cobots as robotic equipment safe enough for interacting with human workers. Twenty years later, collaborative robots are highly demanded in the packaging industry, and have already been massively adopted by companies facing issues for meeting customer demands. Meantime, cobots are still making they way into environments where value-added tasks require more complex interactions between robots and human operators. For other applications like a rescue mission in a disaster scenario, robots have to deal with highly dynamic environments and uneven terrains. All these applications require robust, fine and fast control of the interaction forces, specially in the case of locomotion on uneven terrains in an environment where unexpected events can occur. Such interaction forces can only be modulated through the control of joint internal torques in the case of under-actuated systems which is typically the case of mobile robots. For that purpose, an efficient low level joint torque control is one of the critical requirements, and motivated the research presented here. This thesis addresses a thorough model analysis of a typical low level joint actuation sub-system, powered by a Brushless DC motor and suitable for torque control. It then proposes procedure improvements in the identification of model parameters, particularly challenging in the case of coupled joints, in view of improving their control. Along with these procedures, it proposes novel methods for the calibration of inertial sensors, as well as the use of such sensors in the estimation of joint torques

    Torque Sensors for Robot Joint Control

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    Robust tuning of robot control systems

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    The computed torque control problem is examined for a robot arm with flexible, geared, joint drive systems which are typical in many industrial robots. The standard computed torque algorithm is not directly applicable to this class of manipulators because of the dynamics introduced by the joint drive system. The proposed approach to computed torque control combines a computed torque algorithm with torque controller at each joint. Three such control schemes are proposed. The first scheme uses the joint torque control system currently implemented on the robot arm and a novel form of the computed torque algorithm. The other two use the standard computed torque algorithm and a novel model following torque control system based on model following techniques. Standard tasks and performance indices are used to evaluate the performance of the controllers. Both numerical simulations and experiments are used in evaluation. The study shows that all three proposed systems lead to improved tracking performance over a conventional PD controller

    Source localization using Poisson integrals

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    International audienceThis paper deals with the problem of source localization in diffusion processes via several sensor devices providing pointwise concentration measures; sensors are assumed to be arranged in circular arrays, they can be fixed along the array or they can turn along a circular path defined by the array. The originality of the proposed source localization solution lies in the computation of the gradient and of higher-order derivatives (i. e., the Hessian) from Poisson integrals; in opposition to other solutions published in the literature, this computation does neither require specific knowledge of the solution of the difiusion process, nor the use of probing signals, but only exploits properties of the PDE. The Laplacian of the measured value is null on the studied domain; such an assumption is justified for isotropic diffusive sources in steady-state. The paper also presents some simulation results of a source-seeking torque control law for mobile non-holonomic robots looking for a heat source in a room, where the source is modeled as a small circular region

    An Ontology-Based Expert System for the Systematic Design of Humanoid Robots

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    Die Entwicklung humanoider Roboter ist eine zeitaufwendige, komplexe und herausfordernde Aufgabe. Daher stellt diese Thesis einen neuen, systematischen Ansatz vor, der es erlaubt, Expertenwissen zum Entwurf humanoider Roboter zu konservieren, um damit zukünftige Entwicklungen zu unterstützen. Der Ansatz kann in drei aufeinanderfolgende Schritte unterteilt werden. Im ersten Schritt wird Wissen zum Entwurf humanoider Roboter durch die Entwicklung von Roboterkomponenten und die Analyse verwandter Arbeiten gewonnen. Dieses Wissen wird im zweiten Schritt formalisiert und in Form einer ontologischen Wissensbasis gespeichert. Im letzten Schritt wird diese Wissensbasis von einem Expertensystem verwendet, um Lösungsvorschläge zum Entwurf von Roboterkomponenten auf Grundlage von Benutzeranforderungen zu generieren. Der Ansatz wird anhand von Fallstudien zu Komponenten des humanoiden Roboters ARMAR-6 evaluiert: Sensor-Aktor-Controller-Einheiten für Robotergelenke und Roboterhände
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