Article
Computer Science, Information Systems
Kirill Muravyev, Konstantin Yakovlev
Summary: This study evaluates five open-source topological mapping methods and compares them using novel metrics. The results show that each method has its own advantages and drawbacks, and none of them builds a graph suitable for navigation out of the box.
Article
Chemistry, Multidisciplinary
Luis A. Pineda, Noe Hernandez, Arturo Rodriguez, Ricardo Cruz, Gibran Fuentes
Summary: This article discusses the reasoning support of service robots in daily life, comparing the strengths and limitations of deliberative inference and conceptual inference. It also describes the characteristics of the service robot conceptual model and architecture, and demonstrates its implementation on the Golem-III robot.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Information Systems
Lan Zhang, Guangxia Wang, Xiong You, Zhiyong Liu, Lin Ma, Jiangpeng Tian, Mingzhan Su
Summary: This paper presents a conceptual model of cyberspace maps from the perspective of cartography, discussing the characteristics and definition of such maps, as well as the types of map elements and their composition, element-space association, relationship mapping, symbolization, and map expression. The paper compares and analyzes typical maps, providing design suggestions. The aim is to enhance the unified understanding of cyberspace, promote the development of cyberspace mapping theory, and lay the foundation for future research.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
(2023)
Review
Computer Science, Information Systems
Xiaoning Han, Shuailong Li, Xiaohui Wang, Weijia Zhou
Summary: Sensing and mapping surroundings is crucial for a mobile robot. By attaching semantic information to a geometric map, known as a semantic map, robots can act in accordance with human rules, plan and execute advanced tasks, and communicate with humans on a conceptual level. This survey reviews methods for semantic mapping in indoor scenes and discusses challenges and potential future directions in implementing semantic maps for robots.
Article
Geography
Simon Scheider, Tom de Jong
Summary: This article discusses new methods for spatial network analysis, which aim to achieve common analytical goals by establishing quantified relations. The results show that traditional data models are insufficient for answering questions, while the new model provides crucial information for understanding spatial network functionality.
TRANSACTIONS IN GIS
(2022)
Article
Psychology, Multidisciplinary
Sami R. Yousif
Summary: Mental representations are crucial for cognition and understanding how the mind works requires studying both the content and format of these representations. Investigating the format of spatial location representation can provide insights into the redundancy and flexibility across different formats.
PERSPECTIVES ON PSYCHOLOGICAL SCIENCE
(2022)
Article
Engineering, Electrical & Electronic
Yuhai Wei, Hui Zhang, Hang Zhong, Li Liu, Yiming Jiang, Yaonan Wang
Summary: This paper proposes an efficient Double Simultaneous Majorization Particle Filter algorithm for localization and mapping of a mobile robot. By using pose majorization and weight majorization algorithms, the accuracy of robot localization and particle-carried map is improved. The proposed adaptive hierarchical resampling method maintains particles with higher weights.
IEEE SENSORS JOURNAL
(2022)
Article
Automation & Control Systems
Hongseok Cheon, Taehyoung Kim, Byung Kook Kim, Jucheol Moon, Hongjun Kim
Summary: This method proposes an online path refinement approach for mobile robots, which uses sensor data to refine the given path and avoid collisions and local minima. The method is practical in terms of computation time and memory size.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Multidisciplinary Sciences
Gily Ginosar, Ehud D. Karpas, Idan Weitzner, Nachum Ulanovsky
Summary: The perception of 3D space has been extensively studied, but there are conflicting reports on distortions. This study proposes that 3D perception consists of two processes: perception of traveled space and perception of surrounding space. By testing these two aspects on the same subjects, it was found that the perception of traveled space is experience-dependent, while the perception of surrounding space is not affected by experience. This suggests that these two aspects of 3D spatial perception emerge from distinct processes.
SCIENTIFIC REPORTS
(2023)
Article
Automation & Control Systems
Wang Yuan, Zhijun Li, Chun-Yi Su
Summary: The study aims to integrate human detection, robot localization, and motion planning to achieve effective and reliable navigation for mobile service robots.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Business
Omid Faraji, Kaveh Asiaei, Zabihollah Rezaee, Nick Bontis, Ehsan Dolatzarei
Summary: This bibliometric study analyzes the intellectual capital (IC) research from 1975 to 2020 using co-word analysis and social network analysis based on the Web of Science database. The study identifies the most frequent keywords, top-producing country, prolific journal, frequently cited journal, and prolific research institute in IC research. The findings also reveal the variations in frequently used keywords across different geographical regions. This study provides a comprehensive understanding of the current state of IC research, highlights research gaps, and offers suggestions for future studies.
JOURNAL OF INNOVATION & KNOWLEDGE
(2022)
Review
Computer Science, Information Systems
In Lee
Summary: The service robot industry is growing rapidly with the technological advances of the Fourth Industrial Revolution. This study analyzes different types of service robots and their research activities, technological foundation, as well as potential opportunities and challenges for future research.
Article
Robotics
Marija Popovic, Florian Thomas, Sotiris Papatheodorou, Nils Funk, Teresa Vidal-Calleja, Stefan Leutenegger
Summary: This study proposes a framework that utilizes deep learning for depth completion to enhance the ability to map obstacle-free space in 3D environments. Experimental results show that the approach maps significantly more correct free space with relatively low error in different indoor environments compared to using raw data alone.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Review
Behavioral Sciences
Alex Dorfman, Omri Weiss, Zohar Hagbi, Anat Levi, David Eilam
Summary: Social spatial cognition focuses on the interaction between self, place, and partners, emphasizing the impact of the social environment on spatial behavior and the convergence of individual spatial representations into collective spatial behavior. Studies suggest that humans and animals have both cognitive maps of the physical environment and social cognitive maps. Social spatial cognition relies on knowledge of the physical and social environments, with the latter predominantly influencing spatial behavior modulation through dynamic social interactions.
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS
(2021)
Article
Multidisciplinary Sciences
Nicola M. Moloney, Konstantin Barylyuk, Eelco Tromer, Oliver M. Crook, Lisa M. Breckels, Kathryn S. Lilley, Ross F. Waller, Paula MacGregor
Summary: This study maps the spatial proteomes of two African trypanosome species, Trypanosoma brucei and Trypanosoma congolense, providing insights into the molecular basis for diversity within and between these pathogen species. Comparative analysis reveals key routes of parasitic adaptation to different biological niches.
NATURE COMMUNICATIONS
(2023)
Article
Robotics
Shengchao Yan, Tim Welschehold, Daniel Buescher, Wolfram Burgard
Summary: This letter proposes a novel approach using deep reinforcement learning to optimize traffic flow at intersections in mixed traffic situations. The method allows connected autonomous vehicles to yield to other vehicles to improve traffic flow at unsignalized intersections.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Robotics
Adrian Roefer, Georg Bartels, Wolfram Burgard, Abhinav Valada, Michael Beetz
Summary: This article introduces a novel framework that uses symbolic mathematical expressions to model articulated structures, including robots and objects, in a unified and extensible manner. With this framework, robots can execute abstract instructions and solve common robotics tasks.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Robotics
Kshitij Sirohi, Rohit Mohan, Daniel Buescher, Wolfram Burgard, Abhinav Valada
Summary: EfficientLPS is a novel architecture that addresses multiple challenges in segmenting LiDAR point clouds, including sparsity, occlusions, scale-variations, and reprojection errors. It comprises a shared backbone, new panoptic fusion module, and is supervised by the panoptic periphery loss function.
IEEE TRANSACTIONS ON ROBOTICS
(2022)
Article
Robotics
Oier Mees, Lukas Hermann, Erick Rosete-Beas, Wolfram Burgard Burgard
Summary: This article presents an open-source simulated benchmark called CALVIN, which is used to learn long-horizon tasks. CALVIN tasks are more complex and support flexible specification of sensor suites. Evaluation of the agents shows that a baseline model based on multi-context imitation learning performs poorly on CALVIN.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Robotics
Jannik Zuern, Wolfram Burgard
Summary: This paper proposes a self-supervised approach that utilizes audio-visual cues to detect moving vehicles in videos. By employing contrastive learning with corresponding pairs of images and recorded audio, the approach achieves accurate detections of vehicles without the need for manual annotations.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Robotics
Oier Mees, Lukas Hermann, Wolfram Burgard
Summary: This paper conducts an extensive study of the critical challenges in learning language conditioned policies from offline free-form imitation datasets. It identifies architectural and algorithmic techniques that improve performance and presents a novel approach that significantly outperforms the state of the art on challenging language conditioned long-horizon robot manipulation.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Robotics
Nicolai Dorka, Tim Welschehold, Joschka Boedecker, Wolfram Burgard
Summary: This letter proposes a method called Adaptively Calibrated Critics (ACC) to alleviate the bias of low variance temporal difference targets by using recent high variance but unbiased on-policy rollouts. ACC is applied to Truncated Quantile Critics algorithm to regulate the bias with a hyperparameter. ACC achieves state-of-the-art results on the OpenAI gym continuous control benchmark and demonstrates improved performance on various tasks from the Meta-World robot benchmark.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2023)
Article
Robotics
Jose Arce, Niclas Voedisch, Daniele Cattaneo, Wolfram Burgard, Abhinav Valada
Summary: In this work, a novel transformer-based head for point cloud matching and registration is proposed for loop closure detection and registration in LiDAR-based SLAM frameworks. The panoptic information is leveraged during training to improve the matching problem. Extensive evaluations demonstrate that PADLoC achieves state-of-the-art results on multiple real-world datasets.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2023)
Article
Robotics
Kshitij Sirohi, Sajad Marvi, Daniel Buescher, Wolfram Burgard
Summary: This paper introduces a novel task of uncertainty-aware panoptic segmentation, aiming to predict per-pixel semantic and instance segmentations with per-pixel uncertainty estimates. The authors define two novel metrics, uncertainty-aware Panoptic Quality (uPQ) and panoptic Expected Calibration Error (pECE), for quantitative analysis. They propose a top-down Evidential Panoptic Segmentation Network (EvPSNet) with a panoptic fusion module leveraging predicted uncertainties.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2023)
Proceedings Paper
Robotics
Niclas Voedisch, Daniele Cattaneo, Wolfram Burgard, Abhinav Valada
Summary: In this work, we propose CL-SLAM, a novel task that extends the concept of lifelong SLAM from a single dynamically changing environment to sequential deployments in several drastically differing environments. To address this task, we introduce CL-SLAM, which leverages a dual-network architecture to adapt to new environments and retain knowledge from previously visited environments. We compare CL-SLAM to learning-based and classical SLAM methods, and demonstrate the advantages of leveraging online data.
ROBOTICS RESEARCH, ISRR 2022
(2023)
Proceedings Paper
Automation & Control Systems
Kuersat Petek, Kshitij Sirohi, Daniel Buescher, Wolfram Burgard
Summary: This paper presents a novel monocular localization approach that achieves accurate and robust vehicle localization in sparse maps using a sliding-window pose graph and predicted uncertainties. Additionally, the use of differentiable cost maps further improves the accuracy of localization.
2022 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2022)
(2022)
Proceedings Paper
Automation & Control Systems
Iman Nematollahi, Erick Rosete-Beas, Seyed Mahdi B. Azad, Raghu Rajan, Frank Hutter, Wolfram Burgard
Summary: To achieve autonomous skill acquisition, a transformation-based 3D video prediction (T3VIP) approach is proposed, which learns the physical rules governing the 3D world dynamics and is able to predict and reason about future outcomes. The model captures observational cues from image and point cloud domains, and incorporates automatic hyperparameter optimization to leverage the 2D and 3D observational signals. The model produces interpretable 3D models for predicting future depth videos and outperforms 2D baselines in RGB video prediction and visuomotor control.
2022 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)
(2022)
Proceedings Paper
Automation & Control Systems
Johan Vertens, Wolfram Burgard
Summary: In this research, a real-time simulation method for synthesizing photorealistic RGB images and sensor-realistic depth maps is proposed. This method can include dynamic objects and improve the testing and validation of robotic perception systems. By using static samples and multimodal cues from CAD models, realistic images can be synthesized, which has been demonstrated on datasets recorded in different setups.
2022 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)
(2022)
Proceedings Paper
Robotics
Mayank Mittal, Rohit Mohan, Wolfram Burgard, Abhinav Valada
Summary: This paper introduces a life-saving technology using unmanned aerial vehicles equipped with bioradars to identify survivors after natural disasters. The technology requires UAVs to autonomously navigate and land on debris piles. The paper proposes a new landing site detection algorithm and conducts experiments using a synthetic dataset and a simulation environment.
ROBOTICS RESEARCH: THE 19TH INTERNATIONAL SYMPOSIUM ISRR
(2022)
Proceedings Paper
Robotics
Henrich Kolkhorst, Wolfram Burgard, Michael Tangermann
Summary: This paper proposes a novel method to utilize user's brain signals as feedback to decode and rank robot trajectories based on user preferences. The research shows that brain signals measured during observation of a robot's trajectory can effectively reflect the user's target trajectory. Furthermore, user feedback from brain signals can be used to infer trajectory preferences and retrieve target trajectories with comparable performance to explicit behavioral feedback.
ROBOTICS RESEARCH: THE 19TH INTERNATIONAL SYMPOSIUM ISRR
(2022)
Article
Automation & Control Systems
Runwei Guan, Shanliang Yao, Lulu Liu, Xiaohui Zhu, Ka Lok Man, Yong Yue, Jeremy Smith, Eng Gee, Yutao Yue
Summary: With the development of Unmanned Surface Vehicles (USVs), the perception of inland waterways has become significant. Traditional RGB cameras cannot work effectively in adverse weather and at night, which has led to the emergence of 4D millimeter-wave radar as a new perception sensor. However, the radar suffers from water-surface clutter and irregular shape of point cloud. To address these issues, this paper proposes a high-performance panoptic perception model called Mask-VRDet, which fuses features of vision and radar using graph neural network.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Adrien Le Reun, Kevin Subrin, Anthony Dubois, Sebastien Garnier
Summary: This study aims to evaluate the quality and health of aerospace parts using a high-dimensional robotic cell. By utilizing X-ray Computed Tomography devices, the interior of the parts can be reconstructed and anomalies can be detected. A methodology is proposed to assess both the raw process capability and the improved process capability, with three strategies developed to improve the robot behavior model and calibration.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Weiming Ba, Jung-Che Chang, Jing Liu, Xi Wang, Xin Dong, Dragos Axinte
Summary: This paper proposes a hybrid scheme for kinematic control of continuum robots, which avoids errors through tension supervision and accurate piecewise linear approximation. The effectiveness of the controller is verified on different continuum robotic systems.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Gabriele Abbate, Alessandro Giusti, Viktor Schmuck, Oya Celiktutan, Antonio Paolillo
Summary: In this study, a learning-based approach is proposed to predict the probability of human users interacting with a robot before the interaction begins. By considering the pose and motion of the user, the approach labels the robot's encounters with humans in a self-supervised manner. The method is validated and deployed in various scenarios, achieving high accuracy in predicting user intentions to interact with the robot.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Tiago Cortinhal, Eren Erdal Aksoy
Summary: This work presents a new depth-and semantics-aware conditional generative model, named TITAN-Next, for cross-domain image-to-image translation between LiDAR and camera sensors. The model is able to translate raw LiDAR point clouds to RGB-D camera images by solely relying on semantic scene segments, and it has practical applications in fields like autonomous vehicles.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Marios Krestenitis, Emmanuel K. Raptis, Athanasios Ch. Kapoutsis, Konstantinos Ioannidis, Elias B. Kosmatopoulos, Stefanos Vrochidis
Summary: This paper addresses the issue of informative path planning for a UAV used in precision agriculture. By using a non-uniform scanning approach, the time spent in areas with minimal value is reduced, while maintaining high precision in information-dense regions. A novel active sensing and deep learning-based coverage path planning approach is proposed, which adjusts the UAV's speed based on the quantity and confidence level of identified plant classes.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Shota Kokubu, Pablo E. Tortos Vinocour, Wenwei Yu
Summary: In this study, a new modular soft actuator was proposed to improve the support performance of soft rehabilitation gloves (SRGs). Objective evaluations and clinical tests were conducted to demonstrate the effectiveness and functionality of the proposed actuator and SRG.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Jinliang Zhu, Yuanxi Sun, Jie Xiong, Yiyang Liu, Jia Zheng, Long Bai
Summary: This paper proposes an active prosthetic knee joint with a variable stiffness parallel elastic actuation mechanism. Numerical verifications and practical experiments demonstrate that the mechanism can reduce torque and power, thus reducing energy consumption and improving the endurance of the prosthetic knee joint.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Yong You, Jingtao Wu, Yunlong Meng, Dongye Sun, Datong Qin
Summary: A new power-cycling variable transmission (PCVT) is proposed and applied to construction vehicles to improve transmission efficiency. A shift correction strategy is developed based on identifying the changes in construction vehicles' mass and gradient. Simulation results show that the proposed method can correct shift points, improve operation efficiency, and ensure a safer operation process.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Shaorui Liu, Wei Tian, Jianxin Shen, Bo Li, Pengcheng Li
Summary: This paper proposes a two-objective optimization technique for multi-robot systems, addressing the issue of balancing productivity and machining performance in high-quality machining tasks.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Pengchao Ding, Faben Zhu, Hongbiao Zhu, Gongcheng Wang, Hua Bai, Han Wang, Dongmei Wu, Zhijiang Du, Weidong Wang
Summary: We propose an autonomous approaching scheme for mobile robot traversing obstacle stairwells, which overcomes the restricted field of vision caused by obstacles. The scheme includes stair localization, structural parameter estimation, and optimization of the approaching process.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Pedro Azevedo, Vitor Santos
Summary: Accurate detection and tracking of vulnerable road users and traffic objects are vital tasks for autonomous driving and driving assistance systems. This paper proposes a solution for object detection and tracking in an autonomous driving scenario, comparing different object detectors and exploring the deployment on edge devices. The effectiveness of DeepStream technology and different object trackers is assessed using the KITTI tracking dataset.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Benjamin Beiter, Divya Srinivasan, Alexander Leonessa
Summary: Powered exoskeletons can significantly reduce physical workload and have great potential impact on future labor practices. To truly assist users in achieving task goals, a shared autonomy control framework is proposed to separate the control objectives of the human and exoskeleton. Positive Power control is introduced for the human-based controller, while 'acceptance' is used as a measure of matching the exoskeleton's control objective to the human's. Both control objectives are implemented in an optimization-based Whole-Body-Control structure. The results verify the effectiveness of the control framework and its potential for improving cooperative control for powered exoskeletons.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
