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Benchmarking Classical and learning-Based Multibeam Point Cloud Registration

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Benchmarking Classical and Learning-Based Multibeam Point Cl...

IEEE International Conference on robotics and Automation (ICRA)

作者： Li Ling Jun Zhang Nils Bore John Folkesson Anna Wåhlin Division of Robotics Perception and Learning (RPL) KTH Royal Institute of Technology Stockholm Sweden Institute of Computer Graphics and Vision (ICGV) TU Graz Austria Ocean Infinity Västra Frölunda Sweden Department of Marine Sciences University of Gothenburg Sweden

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Deep learning has shown promising results for multiple 3D point cloud registration datasets. However, in the underwater domain, most registration of multibeam echo-sounder (MBES) point cloud data are still performed using classical methods in the iterative closest point (ICP) family. In this work, we curate and release DotsonEast Dataset, a semi-synthetic MBES registration dataset constructed from an autonomous underwater vehicle in West Antarctica. Using this dataset, we systematically benchmark the performance of 2 classical and 4 learning-based methods. The experimental results show that the learning-based methods work well for coarse alignment, and are better at recovering rough transforms consistently at high overlap (20-50%). In comparison, GICP (a variant of ICP) performs well for fine alignment and is better across all metrics at extremely low overlap (10%). To the best of our knowledge, this is the first work to benchmark both learning-based and classical registration methods on an AUV-based MBES dataset. To facilitate future research, both the code and data are made available online. 1

关键词： Point cloud compression learning systems Measurement Three-dimensional displays Simultaneous localization and mapping Iterative closest point algorithm Transforms

Verifying Nonlinear Neural Feedback Systems using Polyhedral Enclosures

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arXiv 2025年

作者： Akinwande, Samuel I. Sidrane, Chelsea Kochenderfer, Mykel J. Barrett, Clark Department of Aeronautical and Astronautical Engineering Stanford University StanfordCA94305 United States Department of Computer Science Stanford University StanfordCA94305 United States Division of Robotics Perception and Learning Intelligent Systems Department School of Electrical Engineering & Computer Science KTH Royal Institute of Technology Stockholm Sweden

As dynamical systems equipped with neural network controllers (neural feedback systems) become increasingly prevalent, it is critical to develop methods to ensure their safe operation. Verifying safety requires extending control theoretic analysis methods to these systems. Although existing techniques can efficiently handle linear neural feedback systems, relatively few scalable methods address the nonlinear case. We propose a novel algorithm for forward reachability analysis of nonlinear neural feedback systems. The approach leverages the structure of the nonlinear transition functions of the systems to compute tight polyhedral enclosures (i.e., abstractions). These enclosures, combined with the neural controller, are then encoded as a mixed-integer linear program (MILP). Optimizing this MILP yields a sound over-approximation of the forward-reachable set. We evaluate our algorithm on representative benchmarks and demonstrate an order of magnitude improvement over the current state of the art. Copyright © 2025, The Authors. All rights reserved.

关键词： Mixed-integer linear programming

FusionPortableV2: A Unified Multi-Sensor Dataset for Generalized SLAM Across Diverse Platforms and Scalable Environments

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arXiv 2024年

作者： Wei, Hexiang Jiao, Jianhao Hu, Xiangcheng Yu, Jingwen Xie, Xupeng Wu, Jin Zhu, Yilong Liu, Yuxuan Wang, Lujia Liu, Ming Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong Robot Perception and Learning Lab Department of Computer Science University College London United Kingdom Shenzhen Key Laboratory of Robotics and Computer Vision Southern University of Science and Technology China Guangzhou China

Simultaneous Localization and Mapping (SLAM) technology has been widely applied in various robotic scenarios, from rescue operations to autonomous driving. However, the generalization of SLAM algorithms remains a significant challenge, as current datasets often lack scalability in terms of platforms and environments. To address this limitation, we present FusionPortableV2, a multi-sensor SLAM dataset featuring sensor diversity, varied motion patterns, and a wide range of environmental scenarios. Our dataset comprises 27 sequences, spanning over 2.5 hours and collected from four distinct platforms: a handheld suite, a legged robot, a unmanned ground vehicle (UGV), and a vehicle. These sequences cover diverse settings, including buildings, campuses, and urban areas, with a total length of 38.7km. Additionally, the dataset includes ground-truth (GT) trajectories and RGB point cloud maps covering approximately 0.3km2. To validate the utility of our dataset in advancing SLAM research, we assess several state-of-the-art (SOTA) SLAM algorithms. Furthermore, we demonstrate the dataset's broad application beyond traditional SLAM tasks by investigating its potential for monocular depth estimation. The completae dataset, including sensor data, GT, and calibration details, is accessible at https://***/dataset/fusionportable v2. Copyright © 2024, The Authors. All rights reserved.

关键词： SLAM robotics

Non-Axiomatic Reasoning for an Autonomous Mobile Robot

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Non-Axiomatic Reasoning for an Autonomous Mobile Robot

IEEE International Conference on robotics and Automation (ICRA)

作者： Patrick Hammer Peter Isaev Lei Feng Robert Johansson Jana Tumova Division of Robotics Perception and Learning KTH Royal Institute of Technology Stockholm Sweden Department of Computer and Information Systems Temple University Philadelphia PA USA Unit of Mechatronics and Embedded Control Systems KTH Royal Institute of Technology Stockholm Sweden Department of Psychology Stockholm University Stockholm Sweden

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

We present the integration of a Non-Axiomatic Reasoning System (NARS) with mobile robots for planning and decision making. NARS enables robots to effectively handle uncertainty in real-time with complete sensor and actuator integration, thereby ensuring adaptability to evolving scenarios. We discuss essential parts of the logic, the architecture and working principles of NARS, and the integration of NARS as a ROS node. A case study is provided demonstrating the system’s proficiency to carry out a garbage collection task in an open-air environment by operating a mobile robot with manipulator arm, and we demonstrate its ability to learn about the place-dependent accumulation of garbage items. Case study also reveals that our approach performs more effectively on the overall task than the Belief-Desire-Intention model we compared with.

关键词： Actuators Uncertainty Object detection Switches Robot sensing systems Manipulators Cognition

Temporally Robust Multi-Agent STL Motion Planning in Continuous Time

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arXiv 2023年

作者： Verhagen, Joris Lindemann, Lars Tumova, Jana The Division of Robotics Perception and Learning School of Electrical Engineering and Computer Science Kth Royal Institute of Technology Stockholm Sweden The Thomas Lord Department of Computer Science University of Southern California Los AngelesCA United States

Signal Temporal Logic (STL) is a formal language over continuous-time signals (such as trajectories of a multiagent system) that allows for the specification of complex spatial and temporal system requirements (such as staying sufficiently close to each other within certain time intervals). To promote robustness in multi-agent motion planning with such complex requirements, we consider motion planning with the goal of maximizing the temporal robustness of their joint STL specification, i.e. maximizing the permissible time shifts of each agent's trajectory while still satisfying the STL specification. Previous methods presented temporally robust motion planning and control in a discrete-time Mixed Integer Linear Programming (MILP) optimization scheme. In contrast, we parameterize the trajectory by continuous Bézier curves, where the curvature and the time-traversal of the trajectory are parameterized individually. We show an algorithm generating continuous-time temporally robust trajectories and prove soundness of our approach. Moreover, we empirically show that our parametrization realizes this with a considerable speed-up compared to state-of-the-art methods based on constant interval time discretization. Copyright © 2023, The Authors. All rights reserved.

关键词： Trajectories

Comparison between Behavior Trees and Finite State Machines

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arXiv 2024年

作者： Iovino, Matteo Förster, Julian Falco, Pietro Chung, Jen Jen Siegwart, Roland Smith, Christian ABB Corporate Research Västerås Sweden Autonomous Systems Lab ETH Zürich Zürich Switzerland Department of Information Engineering University of Padova Italy School of EECS The University of Queensland Australia Division of Robotics Perception and Learning KTH - Royal Institute of Technology Stockholm Sweden

Behavior Trees (BTs) were first conceived in the computer games industry as a tool to model agent behavior, but they received interest also in the robotics community as an alternative policy design to Finite State Machines (FSMs). The advantages of BTs over FSMs had been highlighted in many works, but there is no thorough practical comparison of the two designs. Such a comparison is particularly relevant in the robotic industry, where FSMs have been the state-of-the-art policy representation for robot control for many years. In this work we shed light on this matter by comparing how BTs and FSMs behave when controlling a robot in a mobile manipulation task. The comparison is made in terms of reactivity, modularity, readability, and design. We propose metrics for each of these properties, being aware that while some are tangible and objective, others are more subjective and implementation dependent. The practical comparison is performed in a simulation environment with validation on a real robot. We find that although the robot’s behavior during task solving is independent on the policy representation, maintaining a BT rather than an FSM becomes easier as the task increases in complexity. Copyright © 2024, The Authors. All rights reserved.

关键词： Computer games

Implementing AI in Advanced Recycling of Perovskite Solar Cells

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Implementing AI in Advanced Recycling of Perovskite Solar Ce...

International Multidisciplinary Conference on Computer and Energy Science (SpliTech)

作者： Christopher Iliffe Sprague Víctor de la Asunción-Nadal Alberto García-Fernández Department of Robotics Perception and Learning KTH - Royal Institute of Technology Stockholm Sweden Science for Life Laboratory Stockholm University Solna Sweden Department of Chemistry Division of Applied Physical Chemistry KTH - Royal Institute of Technology Stockholm Sweden Department of Physics and Astronomy Condensed Matter Physics of Energy Materials Division of X-ray Photon Science Uppsala Sweden

ISBN: (数字)9789532901351

ISBN: (纸本)9798350390797

The electrification of society is an essential component of the effort to achieve a fossil-free world, where solar cells will play a central role in the future energy system. The advancement of photovoltaics should be aligned with principles of the circular economy. In the last years, lead halide perovskites have risen as a leading candidate for third-generation solar cells, experiencing rapid advancement. However, the manufacturing of commercial products inevitably generates significant waste and end-of-life devices, leading to potentially severe environmental repercussions. To tackle this challenge, proactive research and development of recycling and recovery technologies for perovskite solar cells are very necessary. Here we introduce a proof of concept, which, to the best of our knowledge, is the first AI-guided method designed to predict the optimal recycling treatment for perovskite solar cells and the first construction of a perovskite recycling dataset. Using sentiment analysis language processing for the first time, we achieved up to 70% accuracy in predicting the correct action for a given device structure. This innovative approach opens up new possibilities for applying sentiment analysis as a tool for e-waste recycling.

关键词： Waste reduction Sentiment analysis Technological innovation Protocols Accuracy Photovoltaic cells Perovskites

Hearing it Out: Guiding Robot Sound Design through Design Thinking

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Hearing it Out: Guiding Robot Sound Design through Design Th...

IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Brian J. Zhang Bastian Orthmann Ilaria Torre Roberto Bresin Jason Fick Iolanda Leite Naomi T. Fitter Collaborative Robotics and Intelligent Systems Institute Oregon State University Corvallis Oregon USA Division of Robotics Perception & Learning KTH Royal Institute of Technology Stockholm Sweden Division of Media Technology & Interaction Design KTH Royal Institute of Technology Stockholm Sweden Music Department Oregon State University Oregon State University Corvallis Oregon USA

Sound can benefit human-robot interaction, but little work has explored questions on the design of nonverbal sound for robots. The unique confluence of sound design and robotics expertise complicates these questions, as most roboticists do not have sound design expertise, necessitating collaborations with sound designers. We sought to understand how roboticists and sound designers approach the problem of robot sound design through two qualitative studies. The first study followed discussions by robotics researchers in focus groups, where these experts described motivations to add robot sound for various purposes. The second study guided music technology students through a generative activity for robot sound design; these sound designers in-training demonstrated high variability in design intent, processes, and inspiration. To unify the two perspectives, we structured recommendations through the design thinking framework, a popular design process. The insights provided in this work may aid roboticists in implementing helpful sounds in their robots, encourage sound designers to enter into collaborations on robot sound, and give key tips and warnings to both.

关键词：

Bots of a Feather: Exploring User perceptions of Group Cohesiveness for Application in Robotic Swarms

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Bots of a Feather: Exploring User Perceptions of Group Cohes...

IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Rebecca Stower Elisabetta Zibetti David St-Onge Division of Robotics Perception and Learning KTH Stockholm Sweden Department of Psychology CHArt-LUTIN Laboratory Paris 8 University Paris France Department of Mechanical Engineering Ecole de Technologie Supérieure Montreal Canada

ISBN: (数字)9781728188591

ISBN: (纸本)9781665406802

Behaviours of robot swarms often take inspiration from biological models, such as ant colonies and bee hives. Yet, understanding how these behaviours are actually perceived by human users has so far received limited attention. In this paper, we use animations to represent different kinds of possible swarm motions intended to communicate specific messages to a human. We explore how these animations relate to the perceived group cohesiveness of the swarm, comprised of five different parameters: synchronising, grouping, following, reacting, and shape forming. We conducted an online user study where 98 participants viewed nine animations of a swarm displaying different behaviours and rated them for perceived group cohesiveness. We found that the parameters of group cohesiveness correlated with the messages the swarm was perceived as communicating. In particular, the message of initiating communication was highly positively correlated with all group parameters, whereas broken communication was negatively correlated. In addition, the importance of specific group parameters differed within each animation. For example, the parameter of grouping was most associated with animations signalling an intervention is needed. These findings are discussed within the context of designing intuitive behaviour for robot swarms.

关键词： Feathers Correlation Shape Biological system modeling Animation Chatbots Robots