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The paper focuses on the stiffness modeling of heavy industrial robots with gravity compensators. The main attention is paid to the identification of geometrical and elastostatic parameters and calibration accuracy. To reduce impact of the…

Robotics · Computer Science 2013-11-28 Alexandr Klimchik , Yier Wu , Claire Dumas , Stéphane Caro , Benoît Furet , Anatol Pashkevich

Calibration of fixtures in robotic work cells is essential but also time consuming and error-prone, and poor calibration can easily lead to wasted debugging time in downstream tasks. Contact-based calibration methods let the user measure…

Robotics · Computer Science 2024-03-05 Rasmus Laurvig Haugaard , Yitaek Kim , Thorbjørn Mosekjær Iversen

The paper focuses on the accuracy improvement of stiffness models for parallel manipulators, which are employed in high-speed precision machining. It is based on the integrated methodology that combines analytical and numerical techniques…

Robotics · Computer Science 2009-09-09 Anatoly Pashkevich , Alexandr Klimchik , Damien Chablat , Philippe Wenger

The paper focuses on the enhanced stiffness modeling of robotic manipulators by taking into account influence of the external force/torque acting upon the end point. It implements the virtual joint technique that describes the compliance of…

Robotics · Computer Science 2009-12-09 Anatoly Pashkevich , Alexandr Klimchik , Damien Chablat

Compliance control is essential for safe physical interaction, yet its adoption is limited by hardware requirements such as force torque sensors. While recent reinforcement learning approaches aim to bypass these constraints, they often…

Robotics · Computer Science 2026-03-03 Haochen Shi , Songbo Hu , Yifan Hou , Weizhuo Wang , Karen Liu , Shuran Song

Flow forming involves complicated tooling/workpiece interactions. Purely analytical models of the tool contact area are difficult to formulate, resulting in numerical approaches that are case-specific. Provided are the details of an…

Classical Physics · Physics 2012-06-13 M. J. Roy , D. M. Maijer , R. J. Klassen , J. T. Wood , E. Schost

Purpose of Review: To effectively synthesise and analyse multi-robot behaviour, we require formal task-level models which accurately capture multi-robot execution. In this paper, we review modelling formalisms for multi-robot systems under…

Robotics · Computer Science 2023-08-16 Charlie Street , Masoumeh Mansouri , Bruno Lacerda

This work presents the design and the corresponding stability analysis of desired model based, joint position constrained, robot controller. Specifically, provided that the initial joint position tracking error signal starts below some…

Systems and Control · Electrical Eng. & Systems 2020-04-27 Samet Gul , Erkan Zergeroglu , Enver Tatlicioglu , Mesih Veysi Kilinc

Many robot manipulation tasks require the robot to make and break contact with objects and surfaces. The dynamics of such changing-contact robot manipulation tasks are discontinuous when contact is made or broken, and continuous elsewhere.…

Robotics · Computer Science 2021-06-22 Saif Sidhik , Mohan Sridharan , Dirk Ruiken

Milling machines form an integral part of many industrial processing chains. As a consequence, several machine learning based approaches for tool wear detection have been proposed in recent years, yet these methods mostly deal with standard…

Machine Learning · Computer Science 2022-02-08 Mahmoud Kheir-Eddine , Michael Banf , Gregor Steinhagen

Robots in real-world environments continuously engage with multiple users and encounter changes that lead to unexpected conflicts in fulfilling user requests. Recent technical advancements (e.g., large-language models (LLMs), program…

Robotics · Computer Science 2024-05-28 Christine P Lee , Pragathi Praveena , Bilge Mutlu

We present the design of a learning-based compliance controller for assembly operations for industrial robots. We propose a solution within the general setting of learning from demonstration (LfD), where a nominal trajectory is provided…

Robotics · Computer Science 2021-11-23 Devesh K. Jha , Diego Romeres , William Yerazunis , Daniel Nikovski

Reinforcement learning shows great potential to solve complex contact-rich robot manipulation tasks. However, the safety of using RL in the real world is a crucial problem, since unexpected dangerous collisions might happen when the RL…

Robotics · Computer Science 2025-05-27 Xiang Zhu , Shucheng Kang , Jianyu Chen

Aligning a lens system relative to an imager is a critical challenge in camera manufacturing. While optimal alignment can be mathematically computed under ideal conditions, real-world deviations caused by manufacturing tolerances often…

Robotics · Computer Science 2025-10-06 Matthias Burkhardt , Tobias Schmähling , Pascal Stegmann , Michael Layh , Tobias Windisch

This letter presents contact-safe Model-based Reinforcement Learning (MBRL) for robot applications that achieves contact-safe behaviors in the learning process. In typical MBRL, we cannot expect the data-driven model to generate accurate…

Robotics · Computer Science 2021-03-10 Cheng-Yu Kuo , Andreas Schaarschmidt , Yunduan Cui , Tamim Asfour , Takamitsu Matsubara

The industrial application motivating this work is the fatigue computation of aircraft engines' high-pressure turbine blades. The material model involves nonlinear elastoviscoplastic behavior laws, for which the parameters depend on the…

Numerical Analysis · Mathematics 2019-08-12 Fabien Casenave , Nissrine Akkari

This paper focuses on sensor fault detection and compensation for robotic manipulators. The proposed method features a new adaptive observer and a new terminal sliding mode control law established on a second-order integral sliding surface.…

Contact can be conceptualized as a set of constraints imposed on two bodies that are interacting with one another in some way. The nature of a contact, whether a point, line, or surface, dictates how these bodies are able to move with…

Robotics · Computer Science 2025-07-24 Andrew S. Morgan , Quentin Bateux , Mei Hao , Aaron M. Dollar

Model-based Reinforcement Learning and Control have demonstrated great potential in various sequential decision making problem domains, including in robotics settings. However, real-world robotics systems often present challenges that limit…

Machine Learning · Computer Science 2023-10-24 Achkan Salehi , Steffen Rühl , Stephane Doncieux

This paper presents a robust path following control method for vehicles that explicitly considers steering resistance dynamics to improve tracking accuracy. Conventional methods typically treat the steering angle as a direct control input;…

Systems and Control · Electrical Eng. & Systems 2026-04-22 Rentaro Iwai , Natsuki Hikasa , Hiroshi Okajima