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IEEE International Conference on robotics and Biomimetics

作者： Longlong Hu Lingqi Tang Hao Chen Yao Li Bing Li Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Shenzhen China Key University Laboratory of Mechanism Machine Theory and Intelligent Unmanned Systems of Guangdong Shenzhen China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Many insects and miniature robots can traverse through narrow spaces via jumping motion; however, successful jumping and landing remains challenging in small-scale. No jumping robot within 90 g have yet demonstrated multiple jumping and perching successfully. Here, we demonstrate continuous jumping and perching of a miniature robot. The origami-inspired structure was manufactured by smart composite microstructure technology. A novel jumping mechanism was designed to load adjustable jump energy actuated by only one motor. A perching mechanism with two adhesive pads was designed to passively couple with the jumping mechanism, achieving perching on the ground and automatically detaching before the next jump. The jumping mechanism achieved adjustable jumping energy, corresponding to jumping height from 0.7 cm to 36.4 cm. The perching mechanism provided successful landing within a wide range (when velocity angle according to vertical direction $=18^{\circ}$ , the velocity magnitude $\leq 3.4\mathrm{m}/\mathrm{s}$ , the body angle $\leq 30^{\circ}$ ). $\text{Unlike}$ typical jumping robots performing uncontrollable landing and free-rolling, our robot kept its body up-righted during the whole movement and avoided free-rolling after landing. The self-contained prototype had 18 g of mass, 6.5 cm of body height, and 36.4 cm of maximum jumping height. Finally, an eccentric motor was integrated to perform multiple omnidirectional jumping and perching movements; this represents significant improvement of motion ability for small-scale mobile robots.

关键词： Insects Biomimetics Prototypes Motors Mobile robots Microstructure

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Adaptive Gait Training of a Lower Limb Rehabilitation Robot Based on Human–Robot Interaction Force Measurement

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Cyborg and Bionic systems 2024年第1期5卷 271-281页

作者： Fuyang Yu Yu Liu Zhengxing Wu Min Tan Junzhi Yu School of Artificial Intelligence University of Chinese Academy of SciencesBeijingChina The Key Laboratory of Cognition and Decision Intelligence for Complex Systems Institute of AutomationChinese Academy of SciencesBeijingChina School of Mechanical Engineering&Automation Northeastern UniversityShenyangChina State Key Laboratory for Turbulence and Complex System Department of Advanced Manufacturing and RoboticsBIC-ESATCollege of EngineeringPeking UniversityBeijingChina

The existing fixed gait lower limb rehabilitation robots perform a predetermined walking trajectory for patients,ignoring their residual muscle *** enhance patient participation and safety in training,this paper aims to develop a lower limb rehabilitation robot with adaptive gait training capability relying on human–robot interaction force ***,a novel lower limb rehabilitation robot system with several active and passive driven joints is developed,and 2 face-to-face mounted cantilever beam force sensors are employed to measure the human–robot interaction ***,a dynamic model of the rehabilitation training robot is constructed to estimate the driven forces of the human lower leg in a completely passive ***,based on the theoretical moment from the dynamics and the actual joint interaction force collected by the sensors,an adaptive gait adjustment method is proposed to achieve the goal of adapting to the wearer’s movement ***,interactive experiments are carried out to validate the effectiveness of the developed rehabilitation training robot *** proposed rehabilitation training robot system with adaptive gaits offers great potential for future highquality rehabilitation training,e.g.,improving participation and safety.

关键词： active passive driven joints lower limb rehabilitation robot human robot interaction adaptive gait training human robot interaction force measurementfirstlya force measurement lower limb rehabilitation robots

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Learning Fast and Precise Pixel-to-Torque Control

arXiv

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arXiv 2022年

作者： Bleher, Steffen Heim, Steve Trimpe, Sebastian Intelligent Control Systems Group Max Planck Institute for Intelligent Systems Stuttgart Germany Biomimetic Robotics Lab Massachusetts Institute of Technology Cambridge United States Institute for Data Science in Mechanical Engineering RWTH Aachen University Aachen Germany

In the field, robots often need to operate in unknown and unstructured environments, where accurate sensing and state estimation (SE) becomes a major challenge. Cameras have been used to great success in mapping and planning in such environments, as well as complex but quasi-static tasks such as grasping, but are rarely integrated into the control loop for unstable systems. Learning pixel-to-torque control promises to allow robots to flexibly handle a wider variety of tasks. Although they do not present additional theoretical obstacles, learning pixel-to-torque control for unstable systems that that require precise and high bandwidth control still poses a significant practical challenge, and best practices have not yet been established. To help drive reproducible research on the practical aspects of learning pixel-to-torque control, we propose a platform that can flexibly represent the entire process, from lab to deployment, for learning pixel-to-torque control on a robot with fast, unstable dynamics: the vision-based Furuta pendulum. The platform can be reproduced with either off-the-shelf or custom-built hardware. We expect that this platform will allow researchers to quickly and systematically test different approaches, as well as reproduce and benchmark case studies from other labs. We also present a first case study on this system using DNNs which, to the best of our knowledge, is the first demonstration of learning pixel-to-torque control on an unstable system with update rates faster than 100 Hz. A video synopsis can be found online at https://***/S2llScfG-8E, and in the supplementary material. © 2022, CC BY.

关键词： Torque control

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Evaluation of visual slam methods in usar applications using ros/gazebo simulation 15th

Evaluation of visual slam methods in usar applications using...

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15th International Conference on Electromechanics and robotics Zavalishin’s Readings, ERZR 2020

作者： Safin, Ramil Lavrenov, Roman Martínez-García, Edgar Alonso Intelligent Robotics Department Higher Institute for Information Technology and Intelligent Systems Kazan Federal University Kazan Russia Laboratorio de Robotica Institute of Engineering and Technology Universidad Autonoma de Ciudad Juarez Ciudad Juarez32310 Mexico

ISBN: (纸本)9789811555794

The problem of determining the position of a robot and at the same time building the map of the environment is referred to as SLAM. A SLAM system generally outputs the estimated trajectory (a sequence of poses) and the map. In practice, it is hard to obtain ground-truth for the map;hence, only trajectory ground-truth is considered. There are various works that provide datasets to evaluate SLAM algorithms in different scenarios including sensor configurations, robots, and environments. Dataset collection in a real-world environment is a complicated task, which requires an elaborate sensor and robot configuration. Different SLAM systems demand various sensors resulting in the problem of finding an appropriate dataset for their evaluation. Thus, in this paper, a solution that is based on ROS/Gazebo simulations is proposed. Two indoor environments with flat and uneven terrain to evaluate laser range and visual SLAM systems are created. Changing the sensor configuration and the environment does not require an elaborate setup. The results of the evaluation for two popular SLAM methods—ORB-SLAM2 and RTAB-Map—are presented. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021.

关键词： Robots

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Is a Simulation better than Teleoperation for Acquiring Human Manipulation Skill Data?

Is a Simulation better than Teleoperation for Acquiring Huma...

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

作者： Donghyeon Kim Seong-Su Park Kwang-Hyun Lee Dongheui Lee Jee-Hwan Ryu Robotics Program Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea Civil and Environmental Engineering Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea Applied Science Research Institute Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea Autonomous Systems Technische Universitat Wien (TU Wien) Vienna Austria

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

This study explores the feasibility of using simulations as a better interface to collect human object manipulation skills for learning from demonstrations (LfD). Recently, numerous researchers have started introducing teleoperation systems to acquire human manipulation skills. However, capturing the subtle, force-involved interaction skills of humans in teleoperation is still challenging due to its inherent dynamic delays and feedback transparency. This research evaluates the effectiveness of demonstration data obtained through simulation versus teleoperation. To evaluate the efficacy of this approach, tasks such as plane cutting, tight peg-in-hole, and deformable pipe plugging were performed to assess the quality of demonstrations acquired. The experimental results highlight the effectiveness of demonstration through simulation in capturing the operator’s force-involved interaction skills. Simulation creates an environment similar to performing tasks with bare hands by minimising dynamic delays due to the exclusion of physical robots and effectively rendering high stiffness. As a result, the demonstration through simulation method has proven effective in extracting interaction data and capturing physical task performance skills.

关键词： Hands Dynamics Rendering (computer graphics) Data models Delays Data mining Intelligent robots

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Analysis of fast prototyping of microcontroller-based ML software for acoustic signal classification

Analysis of fast prototyping of microcontroller-based ML sof...

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Signal Processing Algorithms, Architectures, Arrangements and Applications (SPA)

作者： Filip Marciniak Wojciech Marciniak Tomasz Marciniak Faculty of Computing and Telecommunications Poznan University of Technology Poznań Poland DECYBEL Student Science Club Poznan University of Technology Poznań Poland Faculty of Automatic Control Robotics and Electrical Engineering Institute of Automatic Control and Robotics Division of Electronic Systems and Signal Processing Poznan University of Technology Poznań Poland

The paper analyzes the preparation of software for acoustic signal classification with machine learning techniques for microcontrollers. The design process was tested for three types of devices: Nordic Thingy:53, *** and Arduino Nano 33 BLE Sense Lite. The classifier training process was carried out using the Edge Impulse platform. Experimental studies were carried out for the process of classifying sound signals generated by the vacuum cleaner motor. The results of the training and the model test were presented for different configurations.

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Mode-switching single-pixel imaging via a high-performance perovskite-Si dual-mode photodetector

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Photonics Research 2024年第12期12卷 2873-2880页

作者： YUJIN LIU DONGXU LIN JINGYANG XING HANYAN ZHAO HONGLING WAN HAO WANG ZHONG JI XUELI CHEN Innovation Center for Advanced Medical Imaging and Intelligent Medicine Guangzhou Institute of TechnologyXidian UniversityGuangzhou 510555China Shenzhen Key Laboratory of Intelligent Robotics and Flexible Manufacturing Systems Department of Mechanical and Energy EngineeringSUSTech Energy Institute for Carbon NeutralitySouthern University of Science and TechnologyShenzhen 518055China Center for Biomedical-Photonics and Molecular Imaging Advanced Diagnostic-Therapy Technology and Equipment Key Laboratory of Higher Education Institutions in Shaanxi ProvinceSchool of Life Science and TechnologyXidian UniversityXi’an 710126China

Visible–near-infrared(VIS-NIR)dual-mode imaging can expand the human perception ***,the development of dual-mode image sensors is still challenging due to complex fabrication processes and readout circuit ***,we design a simple-structured(perovskite-Au/Si/Ag)dual-mode *** unique asymmetric electrode design allows the device to support two operating modes at zero *** device exhibits a detection range covering 400–1100 nm under top illumination mode,with a peak specific detectivity of up to 5.56×1013 *** bottom illumination mode,the device demonstrates pronounced narrowband NIR response *** importantly,we develop a dual-mode single-pixel imaging system based on this device,bypassing the fabrication processes of high-density array image *** system exhibits excellent VISNIR dual-mode imaging results,effectively separating NIR and VIS information and enhancing infrared details in the fused ***,we discover that the system can effectively suppress ringing artifacts,achieving infrared information perception at a low sampling rate,which can accelerate the imaging speed by∼16 times(reduced from∼3.2 s to∼0.2 s).Our proposed dual-mode single-pixel imaging technology offers new means for material identification and intelligent perception.

关键词： mode illumination details

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Learning Goal-based Movement via Motivational-based Models in Cognitive Mobile Robots

arXiv

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arXiv 2023年

作者： Berto, Letícia Costa, Paula Simões, Alexandre Gudwin, Ricardo Colombini, Esther Laboratory of Robotics and Cognitive Systems Institute of Computing University of Campinas Brazil Dept. of Computer Engineering and Industrial Automation School of Electrical and Computer Engineering University of Campinas Brazil Dept. of Control and Automation Engineering Institute of Science and Technology São Paulo State University Sorocaba Brazil University of Campinas Brazil

Humans have needs motivating their behavior according to intensity and context. However, we also create preferences associated with each action’s perceived pleasure, which is susceptible to changes over time. This makes decision-making more complex, requiring learning to balance needs and preferences according to the context. To understand how this process works and enable the development of robots with a motivational-based learning model, we computationally model a motivation theory proposed by Hull. In this model, the agent (an abstraction of a mobile robot) is motivated to keep itself in a state of homeostasis. We added hedonic dimensions to see how preferences affect decision-making, and we employed reinforcement learning to train our motivated-based agents. We run three agents with energy decay rates representing different metabolisms in two different environments to see the impact on their strategy, movement, and behavior. The results show that the agent learned better strategies in the environment that enables choices more adequate according to its metabolism. The use of pleasure in the motivational mechanism significantly impacted behavior learning, mainly for slow metabolism agents. When survival is at risk, the agent ignores pleasure and equilibrium, hinting at how to behave in harsh scenarios. Copyright © 2023, The Authors. All rights reserved.

关键词： Metabolism

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Efficient 2D Simulators for Deep-Reinforcement-Learning-based Training of Navigation Approaches

Efficient 2D Simulators for Deep-Reinforcement-Learning-base...

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International Conference on Ubiquitous Robots (UR)

作者： Huajian Zeng Linh Kästner Jens Lambrecht The Chair of Robotics Artificial Intelligence and Real-time Systems Technical University Munich (TUM) Germany The Chair of Industry Grade Networks and Clouds Faculty of Electrical Engineering and Computer Science Berlin Institute of Technology Berlin Germany

In recent years, Deep Reinforcement Learning (DRL) has emerged as a competitive approach for mobile robot navigation. However, training DRL agents often comes at the cost of difficult and tedious training procedures in which powerful hardware is required to conduct oftentimes long training runs. Especially, for complex environments, this proves to be a major bottleneck for widespread adoption of DRL approaches into industries. In this paper we integrate an efficient 2D simulator into the Arena-Rosnav framework of our previous work as an alternative simulation platform to train and develop DRL agents. Therefore, we utilized the provided API to integrate necessary components into the ecosystem of Arena-Rosnav. We evaluated our simulator by training a DRL agent within that platform and compared the training and navigational performance against the baseline 2D simulator Flatland, which is the default simulating platform of Arena-Rosnav. Results demonstrate that using our Arena2D simulator results in substantially faster training times and in some scenarios better agents. This proves to be an important step towards resource-efficient DRL training, which accelerates training times and improve the development cycle of DRL agents for navigation tasks. We made our simulator openly available at https://***/Arena-Rosnav/arena2d.

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At school with a robot: Italian students’ perception of robotics during an educational program.

At school with a robot: Italian students’ perception of rob...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Francesca Cocchella Giulia Pusceddu Giulia Belgiovine Michela Bogliolo Linda Lastrico Maura Casadio Francesco Rea Alessandra Sciutti CONTACT unit Italian Institute of Technology Genoa Italy Department of Computer Science Bioengineering Robotics and Systems Engineering (DIBRIS) University of Genova Genova Italy RBCS unit Italian Institute of Technology Genoa Italy Scuola di Robotica Genoa Italy

Social robots are expected to become more and more used in the education field. However, in the interaction between children and social robots, how robots are perceived in social contexts is still under investigation. In this exploratory study, we aimed to investigate how children’s expectations and demographical characteristics (N= 53, 9-14 years old) influence their perception of robot NAO during an education training program in schools. MANCOVA analysis conducted over questionnaire data indicates a positive correlation between the acceptance of the robot and the enjoyment of interacting with it. We found evidence that the more students accepted the robot, the more they perceived the group environment positively. Through a Correspondence Analysis, we investigate which are the preferred features of a robot according to the age of participants. The study suggests that a better opinion of robotics is a factor that can improve the learning environment in this specific context. Our exploratory study encourages conducting studies in-the-wild using self-reported measures to understand the implication of Child-Robot Interaction better.

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