1,720,969 research outputs found
Combining Sampling- and Gradient-based Planning for Contact-rich Manipulation
No full textPlanning for contact-rich manipulation involves discontinuous dynamics, which presents challenges to planning methods. Sampling-based planners have higher sample complexity in high-dimensional problems and cannot efficiently handle state constraints such as force limits. Gradient-based solvers can suffer from local optima and their convergence rate is often worse on non-smooth problems. We propose a planning method that is both sampling- and gradient-based, using the Cross-entropy Method to initialize a gradient-based solver, providing better initialization to the gradient-based method and allowing explicit handling of state constraints. The sampling-based planner also allows direct integration of a particle filter, which is here used for online contact mode estimation. The approach is shown to improve performance in MuJoCo environments and the effects of problem stiffness and planing horizon are investigated. The estimator and planner are then applied to an impedance-controlled robot, showing a reduction in solve time in contact transitions to only gradient-based
Outer-Loop Admittance and Motion Control Dual Improvement via a Multi-Function Observer
Full text linkIntegrated Disturbance Observer-Based Robust Force Control
No full textFor robotic tasks that involve combined transmitting and contact force control, achieving high-performance motion control while ensuring stable environment contact is difficult. Among the factors that affect the quality of this force control, we may account vibrations due to misalignment in the mechanical components, actuator inaccuracies, non-linear effects of friction, and backlash. All the above factors can be collectively considered as force disturbances. Towards high-performance motion control and contact stability, a novel integrated disturbance observer (IDOB) is proposed. The IDOB uses force sensor measurements with position measurements and a plant model to isolate and robustly suppress the effects of force disturbances within the plant without compromising contact stability. This is applied here to a force control system to demonstrate the enhanced force control performance in free space and in contact. The passivity, robust stability, and disturbance rejection of the proposed IDOB are compared with those of existing force controllers, with and without force-based DOBs. Finally, actual experiments are conducted in free space and contact under various interaction conditions, showing that the IDOB improves transmitting force control and disturbance suppression performances. Moreover, peak collision force is reduced while maintaining contact stability with stiff environments
Task Space Outer-Loop Integrated DOB-Based Admittance Control of an Industrial Robot
No full textAdmittance control can improve robot performance and robustness in interactive tasks but is still limited by stability when implemented on low-admittance hardware, such as position-controlled industrial robots. This limits applications that require payload, reach, or positioning accuracy. While the idealized reference admittance behavior would be stable with any passive environment (provided positive damping), real robots can be unstable, especially in high-stiffness environments. Thus, instability comes from deviation from the ideal reference model, due to either inner-loop bandwidth, time delay, or other model error. To improve the accuracy of rendered dynamics and reduce contact forces, a novel integrated disturbance observer (DOB)-based admittance control method is proposed. This method does not require access to the robot's inner-loop position control; instead, it is designed and built around it in task space. The task space multisensor information, i.e., the velocity command, measured output velocity, and the force/torque (F/T) sensor measurement are integrated to estimate and robustly suppress the disturbances. Theoretical analyses and experiments on the actual robot show that the proposed method is able to improve admittance tracking accuracy and reduce contact forces even at higher admittance
Differentiable Compliant Contact Primitives for Estimation and Model Predictive Control
No full textControl techniques like MPC can realize contact-rich manipulation which exploits dynamic information, maintaining friction limits and safety constraints. However, contact geometry and dynamics are required to be known. This information is often extracted from CAD, limiting scalability and the ability to handle tasks with varying geometry. To reduce the need for a priori models, we propose a framework for estimating contact models online based on torque and position measurements. To do this, compliant contact models are used, connected in parallel to model multi-point contact and constraints such as a hinge. They are parameterized to be differentiable with respect to all of their parameters (rest position, stiffness, contact location), allowing the coupled robot/environment dynamics to be linearized or efficiently used in gradient-based optimization. These models are then applied for: offline gradient-based parameter fitting, online estimation via an extended Kalman filter, and online gradient-based MPC. The proposed approach is validated on two robots, showing the efficacy of sensorless contact estimation and the effects of online estimation on MPC performance. Video results can be seen at https://youtu.be/CuCTcmn3H-o
A Perturbation-Robust Framework for Admittance Control of Robotic Systems With High-Stiffness Contacts and Heavy Payload
Full text linkApplications involving serial manipulators, in both co-manipulation with humans and autonomous operation tasks, require the robot to render high admittance so as to minimize contact forces and maintain stable contacts with high-stiffness surfaces. This can be achieved through admittance control, however, inner loop dynamics limit the bandwidth within which the desired admittance can be rendered from the outer loop. Moreover, perturbations affect the admittance control performance whereas other system specific limitations such as “black box” PD position control in typical industrial manipulators hinder the implementation of more advanced control methods. To address these challenges, a perturbation-robust framework, designed for serial manipulators engaged in contact-rich tasks involving heavy payloads, is introduced in this paper. Within this framework, a generalized perturbation-robust observer (PROB), which exploits the joint velocity measurements and inner loop velocity control model, and accommodates the varying stiffness of contacts through contact force measurements is introduced. Three PROBs including a novel Combined Dynamics Observer (CDYOB) are presented. The CDYOB can render wide-range admittance without bandwidth limitations from the inner loop. Theoretical analyses and experiments with an industrial robot validate the effectiveness of the proposed method. © 2024 The Authors. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/TRUEsciescopu
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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