Article
Multidisciplinary Sciences
Dezhao Lin, Fan Yang, Di Gong, Ruihong Li
Summary: This study proposes a one-piece-mold folded diaphragm with radial magnetization property to achieve large 3D and bi-directional deformation with inside-volume change capability. The appearance of the diaphragm can be easily customized and implanted into different untethered soft robotic systems. The diaphragm pump and soft robots demonstrated the flexible and rapid locomotion excited by single homogeneous magnetic fields.
NATURE COMMUNICATIONS
(2023)
Article
Robotics
Barry William Mulvey, Thilina Dulantha Lalitharatne, Thrishantha Nanayakkara
Summary: Many animals can adapt their body shape to navigate through narrow gaps in cluttered environments, but most robots lack this capability. This letter proposes a novel design of a deformable mobile robot that can adjust its stance to increase stability or fit through small gaps and flexible obstacles. The robot uses whisker-based feedback control to match its deformation with the obstacle's compliance level. Real-time algorithms are presented for shape adjustment in uncalibrated environments. Results from obstacle navigation tests highlight the importance of integrating environment perception and physical reaction capabilities for improved performance of mobile robots in unstructured environments.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2023)
Article
Computer Science, Artificial Intelligence
Jesus D. Rivero-Ortega, Juan S. Mosquera-Maturana, Josh Pardo-Cabrera, Julian Hurtado-Lopez, David F. Ramirez-Moreno
Summary: This article introduces a bio-inspired navigation system for robots to guide social agents to target locations while avoiding obstacles. The system uses ring attractor neural networks to enable stable activity patterns and effective navigation. The system is compared to the Social Force Model and Rapidly Exploring Random Tree Star methods, and the results show that it outperforms the Social Force Model.
FRONTIERS IN NEUROROBOTICS
(2023)
Review
Engineering, Aerospace
Fang Kong, Yingjing Guo, Jianhua Zhang, Xiaojing Fan, Xiaohan Guo
Summary: This review evaluates the research progress of bio-inspired polarized skylight navigation from the perspectives of theoretical basis, information detection, sensor design, and navigation realization. The review discusses the theory of skylight polarization, measurement results under different weather conditions, the development of bionic polarization navigation sensors, and the algorithms for polarization skylight orientation. The combined application of polarized skylight navigation sensors with other navigation systems is also examined. The review concludes by presenting the future development trends of polarization navigation.
CHINESE JOURNAL OF AERONAUTICS
(2023)
Article
Robotics
Yuzhe Wang, Pengpeng Zhang, Hui Huang, Jian Zhu
Summary: In this study, a fully transparent soft jellyfish robot is developed with both transparency and bio-inspired omni motions in water. The robot is driven by transparent dielectric elastomer actuators (DEAs) using hybrid silver nanowire networks and conductive polymer as compliant electrodes. This transparent DEA allows the robot to achieve vertical and horizontal movements in water, mimicking the pulsating rhythm of a real jellyfish.
Article
Biology
Charlotte Arlt, Roberto Barroso-Luque, Shinichiro Kira, Carissa A. Bruno, Ningjing Xia, Selmaan N. Chettih, Sofia Soares, Noah L. Pettit, Christopher D. Harvey
Summary: By studying the neural activity of mice with different cognitive experiences during a navigation decision task, it was found that past learning is a critical determinant of whether the cortex plays a key role in goal-directed navigation.
Review
Engineering, Multidisciplinary
Pengxiao Bao, Liwei Shi, Lijie Duan, Shuxiang Guo, Zhengyu Li
Summary: With the advancement in camera technology, high-speed cameras have significantly contributed to capturing animal movement and posture, thereby greatly promoting research in experimental biology. Additionally, the growing popularity of bionics among researchers has led to the design of robots incorporating biological features, resulting in increased interest in bio-inspired robots. In comparison to traditional robots, bio-inspired robots mimic the motion patterns of animals to achieve similar propulsion features, which may be more effective and reasonable. This paper categorizes the motion patterns of aquatic animals into four types based on their propulsion mechanisms: drag-based, lift-based, jet-based, and interface-based. It also introduces and reviews bio-inspired robots that imitate aquatic prototypes. Finally, the potential of aquatic bio-inspired robots is discussed.
JOURNAL OF BIONIC ENGINEERING
(2023)
Article
Engineering, Geological
Hosain Bagheri, Daniel Stockwell, Benjamin Bethke, Nana Kwame Okwae, Daniel Aukes, Junliang Tao, Hamid Marvi
Summary: This study presents a bio-inspired burrowing robot and explores its burrowing behavior in glass beads. The study found that the four-bladed screw provides higher translational velocity but comes at the expense of higher motor torque and power, resulting in higher cost of transport. Additionally, operating the one-bladed screw at a lower rotational speed provides lower cost of transport. The tubercled fin design showed promising results in decreasing vertical drag and increasing translational velocity during burrowing.
Article
Robotics
Wen-Bo Li, Xin-Yu Guo, Wen-Ming Zhang
Summary: Natural animals inspire soft robot designs, with a small stomatopod species known as Nannosquilla decemspinosa exhibiting a unique backward somersaulting locomotion. Scientists have developed a bio-inspired dynamic somersaulting soft robot, which moves at a much faster speed than other fast-moving soft robots, showcasing the great potential of the dynamic somersaulting mechanism for designing highly mobile soft locomotion robots.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Article
Engineering, Electrical & Electronic
Peng Xu, Jianhua Liu, Xiangyu Liu, Xinyu Wang, Jiaxi Zheng, Siyuan Wang, Tianyu Chen, Hao Wang, Chuan Wang, Xianping Fu, Guangming Xie, Jin Tao, Minyi Xu
Summary: A self-powered triboelectric palm-like tactile sensor is designed to mimic the structure and texture of sea otters' palms, enabling real-time detection of external loads underwater and high-frequency contact stability, making it a promising tool for underwater tasks.
NPJ FLEXIBLE ELECTRONICS
(2022)
Article
Robotics
Fangwen Yu, Yujie Wu, Songchen Ma, Mingkun Xu, Hongyi Li, Huanyu Qu, Chenhang Song, Taoyi Wang, Rong Zhao, Luping Shi
Summary: The research report introduces a brain-inspired general place recognition system called NeuroGPR, which enables robots to recognize places in natural environments by mimicking the neural mechanism of multimodal sensing, encoding, and computing. The system utilizes a multimodal hybrid neural network to encode and integrate cues from different sensors, and a multiscale liquid state machine to process and fuse the information. Experimental results show that NeuroGPR performs well in various environmental conditions.
Article
Robotics
Tingting Sui, Ting Zou, Daniel Riskin
Summary: This study proposes a design of a UAV that can mimic flight behaviors of bats inspired by their agility, high efficiency, and low noise. By adjusting wing flapping and morphing, the UAV achieves sufficient lift and thrust forces for versatile maneuvers. A multi-objective optimization method is used to determine wing positions and elbow angles, minimizing the differences between biological bat trajectories and those of the robot. The proposed method provides a straightforward and robust approach for optimizing bat-inspired robots.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Multidisciplinary Sciences
Naveen Sendhilnathan, Debaleena Basu, Michael E. Goldberg, Jeffrey D. Schall, Aditya Murthy
Summary: The study revealed unexpected differences in neural signatures for goal-directed versus non-goal-directed movements in a brain area selectively implicated in voluntary control, adding critical constraints to the way we think about saccade generation in the brain.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2021)
Article
Computer Science, Artificial Intelligence
Xuelong Sun, Qinbing Fu, Jigen Peng, Shigang Yue
Summary: Autonomous navigation, consisting of goal approaching and collision avoidance, is a fundamental and crucial capacity of robots and animals. Researchers and engineers have been fascinated by insect-inspired solutions for these two key problems in navigation. However, previous studies have only focused on one of the problems at a time. In this study, an insect-inspired algorithm is proposed to integrate both goal approaching and collision avoidance mechanisms, resulting in robust and efficient navigation performance. This study represents an important step towards a coordinated control system that combines different functionalities of insect-like navigation.
Article
Green & Sustainable Science & Technology
Jiwen Guan, Yanzhao Su, Ling Su, C. B. Sivaparthipan, BalaAnand Muthu
Summary: The biologically inspired algorithm is crucial in industrial robot control, with the proposed Bio-inspired Intelligent Industrial Robot Control System (BIIRCS) utilizing Deep Learning methods to achieve high performance in tasks such as object recognition and action planning. The study demonstrates the potential of intelligent systems created using Deep Learning algorithms and industrial robotics, showing improved performance compared to existing approaches.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2021)
Article
Robotics
Sourav Garg, Niko Suenderhauf, Michael Milford
Summary: This paper presents a novel system that overcomes the challenges in place recognition, which include limited observable visual content, significant viewpoint changes, and radical appearance changes. By utilizing a hybrid image descriptor, keypoint correspondences, and normalization techniques, the system achieves practical performance where existing state-of-the-art methods fail.
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
(2022)
Article
Robotics
Dimity Miller, Niko Sunderhauf, Michael Milford, Feras Dayoub
Summary: In this paper, we propose GMM-Det, a real-time method for extracting epistemic uncertainty from object detectors to identify and reject open-set errors. GMM-Det trains the detector to produce a structured logit space that is modeled with class-specific Gaussian Mixture Models. Experimental results show that GMM-Det consistently outperforms existing uncertainty techniques for identifying and rejecting open-set detections.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Robotics
Bruno Arcanjo, Bruno Ferrarini, Michael Milford, Klaus D. McDonald-Maier, Shoaib Ehsan
Summary: This study introduces an extremely compact and efficient visual place recognition algorithm, utilizing a voting mechanism that combines multiple small and efficient classifiers to achieve more robust and consistent results compared to a single classifier.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Robotics
Ahmad Khaliq, Michael Milford, Sourav Garg
Summary: In this paper, the authors propose an improved NetVLAD representation learning method, which utilizes a low-resolution image pyramid encoding to obtain richer place representations. The resulting multi-resolution feature pyramid can be easily aggregated using the VLAD algorithm, eliminating the need for concatenating or summing multiple patches. Experimental results demonstrate that the proposed method achieves state-of-the-art performance in global descriptor-based retrieval.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Robotics
Connor Malone, Sourav Garg, Ming Xu, Thierry Peynot, Michael Milford
Summary: This research improves road segmentation based on similar places by eliminating limitations of traditional methods. By using Visual Place Recognition to find similar places and integrating a novel segmentation quality metric, the system achieves state-of-the-art road segmentation performance in multiple challenging scenarios, without the need for prior training or access to the same geographical locations.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Automation & Control Systems
Tobias Fischer, Wolf Vollprecht, Silvio Traversaro, Sean Yen, Carlos Herrero, Michael Milford
IEEE ROBOTICS & AUTOMATION MAGAZINE
(2022)
Article
Robotics
Bruno Ferrarini, Michael J. Milford, Klaus D. McDonald-Maier, Shoaib Ehsan
Summary: This article proposes a new class of highly compact models for visual place recognition (VPR) on resource-constrained platforms. By decreasing the precision of model parameters, reducing network depth, and decreasing the number of neurons in the classifier stage, the proposed models significantly reduce memory requirements and computational effort while maintaining state-of-the-art VPR performance.
IEEE TRANSACTIONS ON ROBOTICS
(2022)
Article
Communication
Mike Milford
Summary: In 2021, the creation and subsequent demise of the Euro Super League highlighted the power of collective rhetoric, particularly the use of kategoria as a form of accusation against the league's owners. The supporters of the six English Premier League clubs positioned themselves as moral authorities, criticizing the owners for their greed and disconnect from the spirit of English soccer. This case demonstrates the intersection of community, morality, and simplified moral issues in contemporary sports.
COMMUNICATION & SPORT
(2023)
Article
Hospitality, Leisure, Sport & Tourism
Mike Milford, Taylor J. Hendrickson
Summary: This research examines the role of Roger Bannister as a representative figure of the British identity and how parliament used him to shape and manage the country's image. The findings reveal the idealization of Bannister as a symbol of Britain's excellence and emphasize the need for careful management of his status. Athletes like Bannister are seen as instrumental in serving national purposes of identity construction and representation.
Article
Robotics
Tobias Fischer, Michael Milford
Summary: Event cameras are of interest due to their characteristics such as high dynamic range, low latency, minimal motion blur, and energy efficiency. This letter explores the distinctiveness of event streams from a small subset of pixels for visual place recognition, demonstrating effectiveness in matching query observations to reference places.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Robotics
Stephen Hausler, Ming Xu, Sourav Garg, Punarjay Chakravarty, Shubham Shrivastava, Ankit Vora, Michael Milford
Summary: 6-DoF visual localization systems use 3D geometry to estimate camera pose accurately. By using hierarchical pipelines and learned 2D feature extractors, scalability and performance can be improved. This study investigates the usage of place-specific configurations to enhance worst-case localization performance, and demonstrates its effectiveness on the Ford AV benchmark dataset.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Robotics
Helen Carson, Jason J. Ford, Michael Milford
Summary: The research demonstrates a new supervised learning approach to predict localization integrity on a frame-by-frame basis, improving the average localization accuracy.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Robotics
Krishan Rana, Vibhavari Dasagi, Jesse Haviland, Ben Talbot, Michael Milford, Niko Sunderhauf
Summary: BCF is a hybrid control strategy that combines traditional hand-crafted controllers with model-free deep reinforcement learning. By fusing uncertainty-aware distributional outputs, BCF arbitrates control between the two systems and achieves better performance. It accelerates learning and ensures safe exploration and deployment.
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
(2023)
Proceedings Paper
Automation & Control Systems
Bruno Ferrarini, Michael Milford, Klaus D. McDonald-Maier, Shoaib Ehsan
Summary: This paper proposes a BNN model based on depthwise separable factorization and binarization for VPR, aiming to replace the first convolutional layer and improve computational and energy efficiency while maintaining accuracy.
2022 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)
(2022)
Article
Computer Science, Information Systems
Mihnea-Alexandru Tomita, Mubariz Zaffar, Bruno Ferrarini, Michael J. Milford, Klaus D. McDonald-Maier, Shoaib Ehsan
Summary: This paper conducts an in-depth investigation into the relationship between the performance of single-frame-based place matching techniques and the use of sequence-based filtering. It analyzes the trade-offs, properties, and limitations of different combinations and demonstrates the benefits of sequence-based filtering for VPR accuracy and time efficiency.
