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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Alibekov, Ulugbek Banerjee, Avijit Satpute, Sumeet Gajanan Nikolakopoulos, George ERASMUS MUNDUS JOINT MASTER in Intelligent Field Robotic Systems Faculty of Informatics Eötvös Loránd University Budapest Hungary Robotics and AI research group Department of Computer Science Electrical and Space Engineering Luleå University of Technology Luleå Sweden

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

This article presents an onboard perception-assisted high-fidelity simulation framework for autonomous planetary soft-landing, enabling visual information processing tightly integrated with advanced onboard guidance system in a realistic simulation environments. Utilizing the open source Unity game engine, a physics-based simulation toolbox integrated with the Robotic Operating System (ROS2), we effectively emulate the motion of spacecraft approaching planetary terrain. The simulation environment features a realistic 3D terrain model and a lander spacecraft equipped with onboard camera to effectively capture detailed local terrain images. The simulation engine accurately captures the spacecraft’s 6-degrees of freedom motion, seamlessly integrating space craft orientation with the associated camera feed while incorporating various illumination conditions using a light source representing the Sun. To demonstrate the efficacy of the framework, we implement a recently developed attitude-constrained minimum jerk guidance algorithm to emulate spacecraft motion. Concurrently, the visual feed from the onboard RGB camera is processed through a gradient extraction-based perception system, providing the visual odometer. This system identifies provably safe landing sites, effectively avoiding potential risks of landing on uneven terrain. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Planetary landers

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Conformal Decision Theory: Safe Autonomous Decisions from Imperfect Predictions

Conformal Decision Theory: Safe Autonomous Decisions from Im...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Jordan Lekeufack Anastasios N. Angelopoulos Andrea Bajcsy Michael I. Jordan Jitendra Malik Department of Statistics UC Berkeley Department of Electrical Engineering and Computer Science UC Berkeley Robotics Institute Carnegie Mellon University

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

We introduce Conformal Decision Theory, a framework for producing safe autonomous decisions despite imperfect machine learning predictions. Examples of such decisions are ubiquitous, from robot planning algorithms that rely on pedestrian predictions, to calibrating autonomous manufacturing to exhibit high throughput and low error, to the choice of trusting a nominal policy versus switching to a safe backup policy at run-time. The decisions produced by our algorithms are safe in the sense that they come with provable statistical guarantees of having low risk without any assumptions on the world model whatsoever; the observations need not be I.I.D. and can even be adversarial. The theory extends results from conformal prediction to calibrate decisions directly, without requiring the construction of prediction sets. Experiments demonstrate the utility of our approach in robot motion planning around humans and robot manufacturing.

关键词： Robot motion Pedestrians Machine learning algorithms Decision theory Switches Prediction algorithms Throughput

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Architecture and Control Simulation for Improved System Resiliency of a Building Microgrid

Architecture and Control Simulation for Improved System Resi...

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Annual Meeting Industrial and Commercial Power Systems Technical Conference

作者： Alexandre F. M. Correia José M. B. Lopes A. Paulo Coimbra Pedro Moura Aníbal T. de Almeida Department of Electrical and Computer Engineering Institute of System and Robotics University of Coimbra Coimbra Portugal

The increasing frequency of natural disasters has led to situations where small towns and critical infrastructure, become isolated from the main utility grid. The microgrids’ ability to work autonomously from the utility grid presents a viable solution to this problem. Microgrid resiliency is the characteristic related to the capacity of a microgrid to minimize the impact of disruptive events and ensure that the power supply is maintained under a variety of adverse conditions. This is specially important for critical infrastructures such as hospitals, communications and military bases. The objective of this paper is to simulate strategies and propose an algorithm for the design and management of electric microgrids with a focus on resiliency towards critical and disaster situations. The proposed solutions will be simulated, using a building microgrid implemented in the University of Coimbra as a pilot. As a result of the work, the study presents an algorithm that efficiently manages loads of a microgrid in order to increase its resilience when the microgrid is isolated from the utility grid.

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Exploring Player's Body as a Game Controller for Fitness Activity Promotion

Exploring Player's Body as a Game Controller for Fitness Act...

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Experiment@ International Conference (exp.at)

作者： Diogo Simões Paulo Menezes Electrical and Computer Engineering Department University of Coimbra Institute of Systems and Robotics Coimbra Portugal

ISBN: (数字)9798350314403

ISBN: (纸本)9798350314410

In recent years, there has been a tendency for people to resort to a more sedentary lifestyle, which has only been aggravated by the COVID-19 pandemic and the evermore common remote work policies. This lack of physical activity brings negative health outcomes and can generally be difficult to overcome due to how challenging it can be for a person to find the motivation to adopt a more physically active routine. To address this issue, we propose the use of serious games as an engaging, fun, and highly motivational tool that can aid people in their quest for a healthier lifestyle. We focus on three problem areas: motor control improvement and rehabilitation, post-stroke rehabilitation, and physical activity for general health. There exist multiple solutions for these problems which often require specific equipment that may not be available to the common user. Therefore, we propose a different approach requiring solely a laptop equipped with a camera, thus making it more practical and accessible to the wider public.

关键词： COVID-19 Motor drives Portable computers Pandemics Games Cameras Remote working

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Monocular Person Localization with Lidar Fusion for Social Navigation

Monocular Person Localization with Lidar Fusion for Social N...

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European Conference on Mobile Robots (ECMR)

作者： Sedat Dogru Carlos A. Silva Lino Marques Department of Electrical and Computer Engineering Institute of Systems and Robotics University of Coimbra Coimbra Portugal

Smooth social navigation requires not only detection of the people around the robot, but also accurate localization of the people, a process difficult to achieve with a single sensing modality. Hence, literature has focused on various fusion approaches, such as RGB-D, ROI based lidar vision fusion, or Artificial Neural Network (ANN) based lidar vision fusion. However, monocular photogrammetry has always been ignored in the literature. In this work, we propose a fusion approach based on monocular positon estimation and lidar, and show the effectivenes of the approach both on a public dataset and a purpose built dataset with different cameras.

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M3ED: Multi-Robot, Multi-Sensor, Multi-Environment Event Dataset

M3ED: Multi-Robot, Multi-Sensor, Multi-Environment Event Dat...

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2023 IEEE/CVF Conference on computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Chaney, Kenneth Cladera, Fernando Wang, Ziyun Bisulco, Anthony Hsieh, M. Ani Korpela, Christopher Kumar, Vijay Taylor, Camillo J. Daniilidis, Kostas University of Pennsylvania GRASP Laboratory PA19104 United States Robotics Research Center Department of Electrical Engineering and Computer Science United States Military Academy West PointNY10996 United States

ISBN: (纸本)9798350302493

We present M3ED, the first multi-sensor event camera dataset focused on high-speed dynamic motions in robotics applications. M3ED provides high-quality synchronized and labeled data from multiple platforms, including ground vehicles, legged robots, and aerial robots, operating in challenging conditions such as driving along off-road trails, navigating through dense forests, and performing aggressive flight maneuvers. Our dataset also covers demanding operational scenarios for event cameras, such as scenes with high egomotion and multiple independently moving objects. The sensor suite used to collect M3ED includes high-resolution stereo event cameras (1280×720), grayscale imagers, an RGB imager, a high-quality IMU, a 64-beam LiDAR, and RTK localization. This dataset aims to accelerate the development of event-based algorithms and methods for edge cases encountered by autonomous systems in dynamic environments. © 2023 IEEE.

关键词： Cameras

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Nonsmooth Dynamic Modeling of a Humanoid Robot with Parallel Mechanisms 16th

Nonsmooth Dynamic Modeling of a Humanoid Robot with Paral...

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16th International Conference on Intelligent robotics and Applications, ICIRA 2023

作者： Xiong, Jiaming Liang, Dingkun Wang, Xin Huang, Yongshan Xie, Anhuan Gu, Jason Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Lab Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China Department of Electrical and Computer Engineering Dalhousie University HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9789819964918

This paper establishes a nonsmooth dynamic model for a humanoid robot with parallel mechanisms. Firstly, the constraint equations of the parallel mechanism are derived through kinematic analysis. By combining the links involved in closed-loop constraints into aggregate nodes, the topology of the robot can be equivalent to a tree structure. Equivalent physical quantities for the aggregate nodes are defined to unify their treatment with individual nodes during dynamic modeling. Subsequently, the contact and impact dynamics of the robot are modeled using constraint-based methods, with a frictional multiple impacts model employed for impacts. Due to the high degree of freedom of the robot, recursive methods are adopted to calculate the corresponding dynamic matrices. Finally, numerical examples are provided to illustrate the dynamic model of the robot. A comparison with the compliance-based methods of Simscape Multibody demonstrates that our dynamic model can reflect more realistic physical processes, providing a more accurate simulation environment for the motion control of the robot. The simulation of standing balance control is also performed based on our dynamic model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Anthropomorphic robots

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A Rigid-Flexible Coupling Recursive Formulation for Dynamic Modeling of Biped Robots 16th

A Rigid-Flexible Coupling Recursive Formulation for Dynamic...

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16th International Conference on Intelligent robotics and Applications, ICIRA 2023

作者： Tang, Lingling Liang, Dingkun Wang, Xin Xie, Anhuan Gu, Jason Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Laboratory Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China Department of Electrical and Computer Engineering Dalhousie University HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9789819964796

Biped robots are complex rigid-flexible coupling multibody systems that achieve the desired stable locomotion through foot-ground interactions. In the recent bio-inspired structure designs for biped robots, flexible parts are usually adopted to absorb the foot-ground impact and store the contact energy. However, most existing modeling formulations can only treat biped robots as rigid multibody systems, and the flexible parts are simply replaced by some linear or torsion springs. Since the deformations of the flexible parts have significant effects on the dynamic responses of the biped robot, the rigid multibody modeling method inevitably leads to a gap between the simulation model and the real prototype, and makes the sim-to-real transfer more difficult. To address this problem, a rigid-flexible coupling recursive modeling formulation is presented in this paper. In addition, the foot-ground interaction is modeled via a smooth normal contact model and a velocity-based Coulomb friction model. Finally, several numerical examples including inverse dynamics, kinematic closed-loop and frictional contact are given to verify the rigid-flexible coupling formulation. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Machine design

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Semi-Autonomous Interaction Framework for Contact-Based Operations with Commercial UAVs IN GNSS-Denied Environments

Semi-Autonomous Interaction Framework for Contact-Based Oper...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： A. González-Morgado Q. Zhang G. Damigos E. Cuniato T. Hui E. Sahin G. Nikolakopoulos R. Siegwart M. Fumagalli A. Ollero G. Heredia GRVC Robotics Labs University of Seville Spain 3D Media Group Tampere University Finland Department of Computer Electrical and Space Ericsson Research and the Robotics and AI Group Autonomous Systems Lab (ASL) at ETH Zurich Switzerland Department of Electrical and Photonics Engineering Technical University of Denmark Denmark Department of Computer Electrical and Space Robotics and AI Group

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

Unmanned aerial vehicles (UAVs) are being increasingly established for autonomous contacted-based inspection of industrial assets, reducing the risk of errors by human operators. However, challenges remain in the navigation under unreliable Global Navigation Satellite System (GNSS) signals, or in the detection and interaction with the inspection surface, which limits the autonomy level of current UAV industrial technologies. This paper presents a semi-autonomous framework which combines automated target detection and interaction in GNSS-denied environments, with supervision commands by a human operator, to increase both safety and reliability. Our framework is composed of: (i) a camera-based onboard odometry solution for positioning the UAV in GNSSdenied conditions, (ii) a target-detection and filtering algorithm which estimates the orientation and position of the interaction target and (iii) a visual servoing strategy for approaching and contacting the target. The proposed framework is developed completely in ROS, and can be used with any commercial UAV. The framework is validated through outdoor flights, where a UAV detects and contacts a target on a vertical pipe.

关键词： Vibrations Global navigation satellite system Three-dimensional displays Switches Inspection Autonomous aerial vehicles Visual servoing Safety Odometry Reliability

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OFF-CLIP: Improving Normal Detection Confidence in Radiology CLIP with Simple Off-Diagonal Term Auto-Adjustment

arXiv

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arXiv 2025年

作者： Park, Junhyun Moon, Chanyu Lee, Donghwan Kim, Kyungsu Hwang, Minho Department of Robotics and Mechatronics Engineering DGIST Korea Republic of Department of Electrical Engineering and Computer Science DGIST Korea Republic of Seoul National University Korea Republic of

Contrastive Language-Image Pre-Training (CLIP) has enabled zero-shot classification in radiology, reducing reliance on manual annotations. However, conventional contrastive learning struggles with normal case detection due to its strict intra-sample alignment, which disrupts normal sample clustering and leads to high false positives (FPs) and false negatives (FNs). To address these issues, we propose OFF-CLIP, a contrastive learning refinement that improves normal detection by introducing an off-diagonal term loss to enhance normal sample clustering and applying sentence-level text filtering to mitigate FNs by removing misaligned normal statements from abnormal reports. OFF-CLIP can be applied to radiology CLIP models without requiring any architectural modifications. Experimental results show that OFF-CLIP significantly improves normal classification, achieving a 0.61 Area under the curve (AUC) increase on VinDr-CXR over CARZero, the state-of-the-art zero-shot classification baseline, while maintaining or improving abnormal classification performance. Additionally, OFF-CLIP enhances zero-shot grounding by improving pointing game accuracy, confirming better anomaly localization. These results demonstrate OFF-CLIP’s effectiveness as a robust and efficient enhancement for medical vision-language models. Copyright © 2025, The Authors. All rights reserved.

关键词： Radiology

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