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IEEE Transactions on Artificial Intelligence 2024年第12期5卷 6225-6239页

作者： Teng, Fei Zhang, Jiaming Peng, Kunyu Wang, Yaonan Stiefelhagen, Rainer Yang, Kailun Hunan University School of Robotics National Engineering Research Center of Robot Visual Perception and Control Technology Changsha410082 China Karlsruhe Institute of Technology Institute for Anthropomatics and Robotics Karlsruhe76131 Germany Institute for Visual Computing ETH Zurich Zurich8092 Switzerland

Light field cameras are capable of capturing intricate angular and spatial details. This allows for acquiring complex light patterns and details from multiple angles, significantly enhancing the precision of image semantic segmentation. However, two significant issues arise: 1) The extensive angular information of light field cameras contains a large amount of redundant data, which is overwhelming for the limited hardware resources of intelligent agents. 2) A relative displacement difference exists in the data collected by different microlenses. To address these issues, we propose an omni-aperture fusion model (OAFuser) that leverages dense context from the central view and extracts the angular information from subaperture images to generate semantically consistent results. To simultaneously streamline the redundant information from the light field cameras and avoid feature loss during network propagation, we present a simple yet very effective subaperture fusion module (SAFM). This module efficiently embeds subaperture images in angular features, allowing the network to process each subaperture image with a minimal computational demand of only (∼1\rm GFlops). Furthermore, to address the mismatched spatial information across viewpoints, we present a center angular rectification module (CARM) to realize feature resorting and prevent feature occlusion caused by misalignment. The proposed OAFuser achieves state-of-the-art performance on four UrbanLF datasets in terms of all evaluation metrics and sets a new record of 84.93% in mIoU on the UrbanLF-Real Extended dataset, with a gain of +3.69%. The source code for OAFuser is available at https://***/FeiBryantkit/OAFuser. © 2020 IEEE.

关键词： Semantic Segmentation

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Feedforward control of flat hybrid automata: a behavioral systems theory approach 63

Feedforward control of flat hybrid automata: a behavioral sy...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Zahn, Frederik Kleinert, Tobias Hagenmeyer, Veit Karlsruhe Institute of Technology Institute for Automation and Applied Informatics Karlsruhe Germany Rwth Aachen University Chair of Process Control Engineering Aachen Germany

ISBN: (纸本)9798350316339

Differential flatness has been defined in the literature for continuous time dynamical systems and for discrete time systems. We define flatness of automata from the perspective of behavioral systems theory, and synthesize a flatness definition for hybrid automata. These new definitions allow for feedforward trajectory generation for flat hybrid automata. Additionally, we provide necessary and sufficient conditions of hybrid automaton flatness for different types of continuous state constraints and switching conditions, and how to compute whether a hybrid automaton is flat. We illustrate feedforward trajectory generation based on our findings for a robotic manipulator example. © 2024 IEEE.

关键词： Continuous time systems

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Experimental Evaluation of Model Predictive Mixed-Initiative Variable Autonomy Systems Applied to Human-Robot Teams

Experimental Evaluation of Model Predictive Mixed-Initiative...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Ramesh, Aniketh Braun, Christian Alexander Ruan, Tianshu Rothfuss, Simon Hohmann, Soren Stolkin, Rustam Chiou, Manolis University of Birmingham Extreme Robotics Lab Birmingham United Kingdom Institute of Control Systems Karlsruhe Institute of Technology Karlsruhe Germany

ISBN: (纸本)9798350337020

Adjusting the level of autonomy in human-machine systems (e.g., human-robot systems) holds great potential for achieving high system performance while maintaining operator involvement. To support operators with the task of setting the proper level of autonomy, we present a novel approach to realise a Model Predictive controller that determines the optimal LoA for each tessellation in the robot's path plan based on the estimated performance degradation due environmental adversities. We also report on an experimental evaluation of a mixed-initiative system where both the operator and the Model Predictive controller are in charge of dynamically adjusting the level of autonomy cooperatively while performing a challenging navigational task with a mobile ground robot in a high-fidelity simulation. To this end, we conducted a user study with 15 participants comparing the performance and user experience of the model predictive system with a state-of-the-art system. The results show significant benefits of the model predictive system in terms of a reduction of conflicts for control and an improved user experience. Additionally, there are indications of benefits in terms of robot health and, consequently, performance for the model predictive system. © 2023 IEEE.

关键词： Adaptive automation Levels of automation Levels of autonomy Mixed initiative control Variable autonomy

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Model Predictive fuzzy control of the Degree of Automation Optimizing Robot Health 17

Model Predictive fuzzy Control of the Degree of Automation O...

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17th IEEE International Symposium on Applied Computational Intelligence and Informatics, SACI 2023

作者： Braun, Christian Alexander Ramesh, Aniketh Rothfus, Simon Chiou, Manolis Stolkin, Rustam Hohmann, Soren Karlsruhe Institute of Technology Institute of Control Systems Karlsruhe Germany University of Birmingham Extreme Robotics Lab Birmingham United Kingdom

ISBN: (纸本)9798350321104

Adjusting operator support in human-machine systems is a promising way of combining operator involvement with high overall system performance. Adaptive automation aims to achieve this goal without burdening the operator with the task of selecting and setting the desired amount of support. In this work, two novel adaptive automations are presented. We use the performance measure of 'robot health' to formulate the optimal control problem of maximizing the robot health of a human-robot system through the adaption of operator support to develop two model predictive controllers. The first one considers discrete levels of operator support, or levels of automation, the second one uses the continuous conception of the degree of automation. We report on a proof-of-concept simulation study evaluating the proposed model predictive controllers in a collaborative teleoperation of a mobile robot;the results demonstrate the ability of both model predictive controllers to successfully arbitrate control between the operator and the robot's controller to maximize robot health. © 2023 IEEE.

关键词： Fuzzy control

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Vibrational Feedback for a Teleoperated Continuum Robot with Non-contact Endoscope Localization

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Current Directions in Biomedical Engineering 2024年第1期10卷 17-20页

作者： Fischer, Jonas Andreas, Daniel Beckerle, Philipp Mathis-Ullrich, Franziska Marzi, Christian Friedrich-Alexander-University of Erlangen-Nuremberg Autonomous Systems and Mechatronics Paul-Gordan-Strase 3/5 Erlangen91052 Germany Friedrich-Alexander-University of Erlangen-Nuremberg Autonomous Systems and Mechatronics Erlangen91052 Germany Friedrich-Alexander-University of Erlangen-Nuremberg Surgical Planning and Robotic Cognition Lab Erlangen91052 Germany Karlsruhe Institute of Technology Institute for Anthropomatics and Robotics - Intelligent Process Automation & Robotics Karlsruhe76131 Germany

Limited or absent haptic feedback is reported as a factor hindering the continued adoption of surgical robots. This article presents a proof of concept for vibrotactile feedback integrated into a continuum robot to explore whether such feedback improves spatial perception in surgical settings. The robot is equipped with a capacitive sensor for noncontact endoscope localization, enabling spatial awareness of the robot's tool center point (TCP) within the surgical environment. The data from the sensor is processed and transmitted to a bracelet worn by the user, which generates vibrotactile feedback. The bracelet contains four vibration motors providing tactile cues for navigation and positioning of the robot's TCP. All subsystems are integrated into a unified system to deliver vibrotactile feedback to the user. When the user maneuvers the TCP of the robot near an object, they receive vibrotactile feedback via the bracelet. Thereby, the intensity of vibration increases as the TCP approaches the object, and the direction of the obstacle is mapped on the bracelet. Initial functional tests were performed and prove the functionality of the proposed system. © 2024 by Walter de Gruyter Berlin/Boston.

关键词： Capacitive sensors

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Tightly-Coupled LiDAR-Visual SLAM Based on Geometric Features for Mobile Agents

Tightly-Coupled LiDAR-Visual SLAM Based on Geometric Feature...

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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Cao, Ke Liu, Ruiping Wang, Ze Peng, Kunyu Zhang, Jiaming Zheng, Junwei Teng, Zhifeng Yang, Kailun Stiefelhagen, Rainer Karlsruhe Institute of Technology Institute for Anthropomatics and Robotics Germany Hunan University School of Robotics China Hunan University National Engineering Research Center of Robot Visual Perception and Control Technology China

ISBN: (纸本)9798350325706

The mobile robot relies on SLAM (Simultaneous Localization and Mapping) to provide autonomous navigation and task execution in complex and unknown environments. However, it is hard to develop a dedicated algorithm for mobile robots due to dynamic and challenging situations, such as poor lighting conditions and motion blur. To tackle this issue, we propose a tightly-coupled LiDAR-visual SLAM based on geometric features, which includes two sub-systems (LiDAR and monocular visual SLAM) and a fusion framework. The fusion framework associates the depth and semantics of the multi-modal geometric features to complement the visual line landmarks and to add direction optimization in Bundle Adjustment (BA). This further constrains visual odometry. On the other hand, the entire line segment detected by the visual subsystem overcomes the limitation of the LiDAR subsystem, which can only perform the local calculation for geometric features. It adjusts the direction of linear feature points and filters out outliers, leading to a higher accurate odometry system. Finally, we employ a module to detect the subsystem's operation, providing the LiDAR subsystem's output as a complementary trajectory to our system while visual subsystem tracking fails. The evaluation results on the public dataset M2DGR, gathered from ground robots across various indoor and outdoor scenarios, show that our system achieves more accurate and robust pose estimation compared to current state-of-the-art multi-modal methods. © 2023 IEEE.

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Towards Flexible Manufacturing: Motion Generation Concept for Coupled Multi-Robot Systems

Towards Flexible Manufacturing: Motion Generation Concept fo...

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IEEE International Conference on Automation Science and Engineering (CASE)

作者： Yucheng Tang Wei Shen Ilshat Mamaev Björn Hein Karlsruhe University of Applied Sciences Proximity Robotics & Automation GmbH Robotics Lab (IAR - IPR) Karlsruhe Institute of Technology (KIT) Institute for Anthropomatics and Robotics - Intelligent Process Automation Karlsruhe Germany

This paper presents a motion generation concept with stiffness and path constraints for multi-robot systems in a flexible manufacturing context. An optimization approach using closed-form inverse kinematics solutions is proposed to maximize the Cartesian stiffness, simultaneously preserving the continuity of the joints' movement. We also present an efficient trajectory generation approach combining Particle Swarm Optimization (PSO) and Online Trajectory Generation (OTG) methods. For the sake of synchronization, we assume a 14 Degrees of Freedom (DOF) closed-chain kinematics for the trajectory generation of the dual-robot system. We evaluate the proposed approach on a mock-up of the sheet metal bending task using two coupled Franka Emika robots. The results show that the proposed method increases the stiffness of the robot, as it can apply three times the force compared to benchmark methods before reaching the joint torque limit in the single robot experiments. Furthermore, two physically coupled Panda robots can generate a force of up to 732 N with joint torque limits set to 10%.

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Feedforward control of flat hybrid automata: a behavioral systems theory approach

Feedforward control of flat hybrid automata: a behavioral sy...

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IEEE Conference on Decision and control

作者： Frederik Zahn Tobias Kleinert Veit Hagenmeyer Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Karlsruhe Germany Chair of Process Control Engineering RWTH Aachen University Aachen Germany

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

关键词： Discrete-time systems Sufficient conditions Automata Switches Manipulators control systems Hybrid power systems Trajectory Feedforward systems Dynamical systems

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Enhancing Force Sensing Capabilities in Exoskeleton Interfaces Using Compliant Actuator-Sensor Units - A User Study

Enhancing Force Sensing Capabilities in Exoskeleton Interfac...

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IEEE/RAS-EMBS International Conference on Biomedical robotics and Biomechatronics (BioRob)

作者： Hosam Alagi Nikola Fischer Kai Behrends Iris Ftirst-Walter Jürgen Becker Michael Beigl Franziska Mathis-Ullrich Björn Hein Intelligent Process Automation and Robotics Laboratory (IPR) Institute for Anthropomatics and Robotics (IAR) Karlsruhe Institute of Technology (KIT) Karlsruhe Germany Institute of Telematics (TM) - Pervasive Computing Systems (TECO) at Karlsruhe Institute of Technology (KIT) Karlsruhe Germany Institut fuer Technik der Informationsverarbeitung (ITIV) at Karlsruhe Institute of Technology (KIT) Karlsruhe Germany Department Artificial Intelligence in Biomedical Engineering (AIBE) Friedrich-Alexander University Erlangen-Nürnberg (FAU) Erlangen Germany Karlsruhe University of Applied Sciences Karlsruhe Germany

ISBN: (数字)9798350386523

ISBN: (纸本)9798350386530

Reliable interaction force sensing between an exoskeleton and the human body is crucial for personalized support and efficient control. Poor donning and disturbances during movement lead to lower force measurement quality and thus to unfavorable use. In this work, we present an active smart human-robot interface by utilizing compliant actuator-sensor units (CASUs) that can be worn over clothing. These units combine capacitive force sensing and actuation using Shape-Memory Alloy (SMA) to actively compensate disturbances and improve force measurement by tightening the interface and reestablishing optimal contact. We present a pilot user study with five subjects, investigating the performance of an exoskele-ton interface featuring three integrated CASUs to compensate for non-ideal donning configurations and displacements during daily activities of walking, sitting down, and climbing the stairs. The results for a passive interface show a decrease in holding forces and force signal quality during activities. Our active interface, on the other hand, effectively compensates for disturbances, restoring high signal quality by the mean of peak-to-peak value up to 300% which leads to more distinct signals.

关键词： Legged locomotion Force measurement Cooling Force Exoskeletons Metals Stairs Robot sensing systems Sensors Reliability

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DMD-Based Model Predictive control for a Coupled PDE-ODE System

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IFAC-PapersOnLine 2023年第2期56卷 4258-4263页

作者： Dirk Wolfram Thomas Meurer Chair of Automation and Control Faculty of Engineering Kiel University 24143 Kiel Germany Digital Process Engineering Group Institute for Mechanical Process Engineering and Mechanics Karlsruhe Institute of Technology (KIT) 76187 Karlsruhe Germany

Models resulting from the application of the finite element method (FEM) are usually high dimensional, thus in general preventing the application of optimal control concepts under real-time conditions. In this work a system consisting of the heat equation defined on a 3-dimensional domain with local in-domain thermal actuators is considered, whose modeling results in a coupled PDE-ODE description. Based on simulation data, a data driven reduced order model is determined using the Dynamic Mode Decomposition with control (DMDc). Based on the DMDc model a model predictive control (MPC) approach with state estimator is developed to realize a desired temperture profile on the given domain. The concept is evaluated involving the high-dimensional finite element model as plant model.

关键词： Distributed parameter systems Reduced order model Data-driven control Model predictive control Heat conduction

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