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检索条件"机构=Lab of Robotics and Human-Machine-Interaction"

共 19 条记录，以下是11-20 订阅

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6D Variable Virtual Fixtures for Telemanipulated Insertion Tasks

6D Variable Virtual Fixtures for Telemanipulated Insertion T...

引用

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Stephan Andreas Schwarz Ulrike Thomas Robotics and Human-Machine Interaction Lab Chemnitz University of Technology Chemnitz Germany

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Telemanipulation enables humans to perform tasks in dangerous environments without exposing them to any risk. The COVID-19 pandemic sadly showed, that these environments can also include the treatment and interaction with infected patients. Since human-robot interactions demand for low interaction forces yet high precision, telemanipulation often results in a high mental workload for the operator. To overcome this, we present a virtual guidance approach to perform telemanipulated insertion tasks. A nasopharyngeal swap sampling procedure is taken as use case. We extend our previously presented approach by adding an additional position fixture, introducing distance-dependent variable stiffness values and guaranteeing stability using energy tanks. Based on RGB-D data, the operator is guided towards a desirable insertion line while approaching the nostril. The distance-dependent stiffness values increase the smoothness of the fixture. Since variable stiffness values can result in unstable behavior, energy tanks for the fixtures are introduced. Experiments show the improvements compared to our previous approach. Further, a comparison between guided and unguided samplings performed by an expert user gives a first impression of the improvements resulting from the fixture.

关键词： Torque Pandemics Fixtures Force Force feedback human-robot interaction Stability analysis Vectors End effectors Intelligent robots

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A Novel Compact Design of a Lever-Cam based Variable Stiffness Actuator: LC-VSA

A Novel Compact Design of a Lever-Cam based Variable Stiffne...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Hongxi Zhu Ulrike Thomas The Lab of Robotics and Human-Machine-Interaction Chemnitz University of Technology Chemnitz Germany

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Ensuring safe interaction between humans and robots is an important challenge in robotics. In recent years, researchers have developed many different soft robots. One possibility to reach this goal is to integrate mechanical springs into their joints. The forthcoming generation of soft robots will be adaptable for joint stiffness to accommodate various tasks. Consequently, the development of variable stiffness joints (VSA) has become crucial. Among the prevalent approaches for stiffness adjustment, lever mechanisms have been implemented in numerous variable stiffness joints. Nonetheless, the integration of the lever technology into VSA often faces challenges in achieving a compact design. This paper introduces a new mechanically compact design for a novel lever-cam based variable stiffness joint, which has been patent under the grand by the german Patentamt.

关键词： Patents Actuators Soft robotics Task analysis Springs Faces

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Using machine Learning for Material Detection with Capacitive Proximity Sensors

Using Machine Learning for Material Detection with Capacitiv...

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2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Yitao Ding Hannes Kisner Tianlin Kong Ulrike Thomas Lab of Robotics and Human-Machine Interaction Chemnitz University of Technology Chemnitz Germany

ISBN: (数字)9781728162126

ISBN: (纸本)9781728162133

The ability of detecting materials plays an important role in robotic applications. The robot can incorporate the information from contactless material detection and adapt its behavior in how it grasps an object or how it walks on specific surfaces. In this, paper we apply machine learning on impedance spectra from capacitive proximity sensors for material detection. The unique spectra of certain materials only differ slightly and are subject to noise and scaling effects during each measurement. A best-fit classification approach to pre-recorded data is therefore inaccurate. We perform classification on ten different materials and evaluate different classification algorithms ranging from simple k-NN approaches to artificial neural networks, which are able to extract the material specific information from the impedance spectra.

关键词： Training machine learning algorithms machine learning Robot sensing systems Capacitive sensors Sensors Impedance

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Collision Avoidance with Proximity Servoing for Redundant Serial Robot Manipulators

Collision Avoidance with Proximity Servoing for Redundant Se...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Yitao Ding Ulrike Thomas Lab of Robotics and Human Machine-Interaction Chemnitz University of Technology Chemnitz SN Germany

ISBN: (数字)9781728173955

ISBN: (纸本)9781728173962

Collision avoidance is a key technology towards safe human-robot interaction, especially on-line and fastreacting motions are required. Skins with proximity sensors mounted on the robot's outer shell provide an interesting approach to occlusion-free and low-latency perception. However, collision avoidance algorithms which make extensive use of these properties for fast-reacting motions have not yet been fully investigated. We present an improved collision avoidance algorithm for proximity sensing skins by formulating a quadratic optimization problem with inequality constraints to compute instantaneous optimal joint velocities. Compared to common repulsive force methods, our algorithm confines the approach velocity to obstacles and keeps motions pointing away from obstacles unrestricted. Since with repulsive motions the robot only moves in one direction, opposite to obstacles, our approach has better exploitation of the redundancy space to maintain the task motion and gets stuck less likely in local minima. Furthermore, our method incorporates an active behaviour for avoiding obstacles and evaluates all potentially colliding obstacles for the whole arm, rather than just the single nearest obstacle. We demonstrate the effectiveness of our method with simulations and on real robot manipulators in comparison with commonly used repulsive force methods and our prior proposed approach.

关键词： Collision avoidance Robot sensing systems Task analysis Manipulators Skin

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Improving Safety and Accuracy of Impedance Controlled Robot Manipulators with Proximity Perception and Proactive Impact Reactions

Improving Safety and Accuracy of Impedance Controlled Robot ...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Yitao Ding Ulrike Thomas Lab of Robotics and Human-Machine-Interaction Chemnitz University of Technology SN Chemnitz Germany

We present a system which improves the safety and accuracy of impedance controlled robotic manipulators with proximity perception. Proximity servoed manipulators, which use proximity sensors attached to the robot’s outer shell, have recently demonstrated robust collision avoidance abilities. Nevertheless, unwanted collisions cannot be avoided entirely. As a fallback safety mechanism, robots with joint force/torque sensing rely on impedance controllers for impact attenuation and compliant behavior. However, impedance controllers induce undesired deflections of the robot from its trajectory when it is not in contact. These deviations are more pronounced at soft configurations and when the robot grasps objects of unknown weight distribution, thus a compromise must be made between high positional accuracy and softness (safety). The proximity information allows the robot to react to anticipated impacts proactively for attenuation and damage reduction of unavoidable collisions, while still maintaining high accuracy during regular operation. This is achieved through variations of impedance parameters according to proximity measurements and motions towards safe joint configurations during the preimpact phase.

关键词： Phase measurement Switches Robot sensing systems Manipulators Attenuation Safety Sensors

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With Proximity Servoing towards Safe human-Robot-interaction

With Proximity Servoing towards Safe Human-Robot-Interaction

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2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Yitao Ding Felix Wilhelm Leonhard Faulhammer Ulrike Thomas Lab of Robotics and Human-Machine-Interaction Chemnitz University of Technology Chemnitz SN Germany

In this paper, we present a serial kinematic robot manipulator equipped with multimodal proximity sensing modules not only on the TCP but distributed on the robot's surface. The combination of close distance proximity information from capacitive and time-of-flight (ToF) measurements allows the robot to perform safe reflex-like and collision-free motions in a changing environment, e.g. where humans and robots share the same workspace. Our methods rely on proximity data and combine different strategies to calculate orthogonal avoidance motions. These motions are instantaneous optimal and are fed directly into the motion controller (proximity servoing). The strategies are prioritized, firstly to avoid collision and then secondly to maintain the task motion if kinematic redundancy is available. The motion is then optimized for avoidance, best manipulability, and smallest end-effector velocity deviation. We compare our methods with common force field based methods.

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human-robot interaction with redundant robots using force-field-dependent variable impedance control

Human-robot interaction with redundant robots using force-fi...

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IEEE International Symposium on robotics and Intelligent Sensors (IRIS)

作者： Florian Müller Felix Weiske Jens Jäkel Ulrike Thomas Jozef Suchy Electrical Engineering and Information Technology Leipzig University of Applied Sciences Chair of Robotics and Human-Machine-Interaction Lab Chemnitz University of Technology

This paper introduces an improvement of the assisting force field (AFF) concept for hand-guiding of robotic arms. The AFF guides the user to several reference paths previously learned from experienced users. The AFF concept is extended to anthropomorphic redundant robots, which are used to obtain more flexibility. The redundancy of the robot is used for collision avoidance with the robot's elbow. The motion for collision avoidance should have a low influence on position and orientation of the end effector. A corresponding algorithm is proposed. Using AFF, a force-field-dependent variable impedance controller (FF-VIC) is developed for reducing the settling time and improving the user comfort. For investigating these proposed developments a simulation study was performed in which user comfort and control performance were evaluated. Analyzing the simulation results, a suitable parametrization for the FF-VIC can be found which improves user comfort and settling time. Finally, the results were experimentally validated and the functionality of the collision avoidance is shown.

关键词： Force Collision avoidance Robot sensing systems Wrist Impedance Service robots

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Gesture Based Symbiotic Robot Programming for Agile Production

Gesture Based Symbiotic Robot Programming for Agile Producti...

引用

IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications

作者： Carl Gä bert Achraf Djemal Hiba Hellara Bilel Ben Atitallah Rajarajan Ramalingame Rim Barioul Dennis Salzseiler Ellen Fricke Olfa Kanoun Ulrike Thomas Robotics and Human-Machine Interaction Lab Chemnitz University of Technology Professorship for Measurements and Sensor Technology Chemnitz University of Technology Chair German Linguistics Semiotics and Multimodal Communication Chemnitz University of Technology

ISBN: (数字)9781665434454

ISBN: (纸本)9781665434461

Agile production lines call for an effective and intuitive way of programming robots. However, traditional approaches rely on providing low-level instructions using either a script-based language or a graphical user interface to export low-level instructions. This, however, can be tedious for assembly tasks. In this work, we present an approach that generates low-level robot control commands from highly abstract communicative hand gestures. In contrast to other works, we use several abstraction layers to generate such commands with as little user input as possible. For this, we use a body-attached multi-sensor setup consisting of a pressure band, a smart glove, EMG and IMU units. Their combined signals define a multi-dimensional vector per time step. We use a Recurrent Neural Network to infer the gesture class from the pre-processed data stream. From these user inputs we generate a set of symbolic spatial relations describing the assembly process. This formal description is then used to select and execute robot skills such as grasping. Hence, we reduce the ambiguity of abstract instructions in several steps and allow for effective gesture-based robot programming. In our work we give insights in defining and detecting such gestures. In addition, we illustrate the functionality of the whole system at real-world examples.

关键词： Symbiosis Tracking Thumb Virtual environments Production Sensor systems Electromyography

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A Unified Perception Benchmark for Capacitive Proximity Sensing Towards Safe human-Robot Collaboration (HRC)

A Unified Perception Benchmark for Capacitive Proximity Sens...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Serkan Ergun Yitao Ding Hosam Alagi Christian Schöffmann Barnaba Ubezio Gergely Soti Michael Rathmair Stephan Mühlbacher-Karrer Ulrike Thomas Björn Hein Michael Hofbaur Hubert Zangl Institute of Smart Systems Technologies Klagenfurt University (AAU) Klagenfurt am Wörthersee Austria Lab of Robotics and Human-Machine-Interaction Chemnitz University of Technology (TUC) Chemnitz Germany Institute for Anthropomatics and Robotics - Intelligent Process Automation and Robotics Lab (IAR - IPR) Karlsruhe Institute of Technology (KIT) Karlsruhe Germany Joanneum Research Robotics (Jr) Institute of Robotics and Mechatronics Klagenfurt am Wörthersee Austria Karlsruhe University of Applied Sciences

During the co-presence of human workers and robots, measures are required to avoid injuries from undesired contacts. Capacitive Proximity Sensors (CPSs) offer a cost-effective solution to cover the entire robot manipulator with fast close-range perception for HRC tasks, closing the perception gap between tactile detection and mid-range perception. CPSs do not suffer from occlusion and compared to pure tactile or force sensing, they react earlier and allow increasing the operating speed of Collaborative Robots (Cobots) while still maintaining safety. However, since capacitive coupling to obstacles varies with their distance, shape and material properties, the projection from capacitance to actual distances is a general problem. In this work, we propose an universal benchmark test procedure for fellow researchers to evaluate their CPSs. Considering ISO/TS 15066 for Power and Force Limiting (PFL) as a reference, we derive the requirements for the specified body regions and propose a method for determining the operation speed to comply with PFL based on a pre-defined detection threshold. Finally, the benchmark test procedure is evaluated on three different concepts of CPSs from the contributed researchers, demonstrating the general applicability.

关键词： Shape Force Collaboration Benchmark testing Robot sensing systems Manipulators Sensors

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