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IEEE International Conference on robotics and Automation (ICRA)

作者： Zach J. Patterson Cosimo Della Santina Daniela Rus Computer Science and Artificial Intelligence Laboratory MIT Department of Cognitive Robotics Delft University of Technology Institute of Robotics and Mechatronics German Aerospace Center (DLR)

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

While much work has been done recently in the realm of model-based control of soft robots and soft-rigid hybrids, most works examine robots that have an inherently serial structure. While these systems have been prevalent in the literature, there is an increasing trend toward designing soft-rigid hybrids with intrinsically coupled elasticity between various degrees of freedom. In this work, we seek to address the issues of modeling and controlling such structures, particularly when underactuated. We introduce several simple models for elastic coupling, typical of those seen in these systems. We then propose a controller that compensates for the elasticity, and we prove its stability with Lyapunov methods without relying on the elastic dominance assumption. This controller is applicable to the general class of underactuated soft robots. After evaluating the controller in simulated cases, we then develop a simple hardware platform to evaluate both the models and the controller. Finally, using the hardware, we demonstrate a novel use case for underactuated, elastically coupled systems in "sensorless" force control.

关键词： Couplings Elasticity Soft robotics Robot sensing systems Market research Hardware Stability analysis

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D-MARL: A Dynamic Communication-Based Action Space Enhancement for Multi Agent Reinforcement Learning Exploration of Large Scale Unknown Environments

D-MARL: A Dynamic Communication-Based Action Space Enhanceme...

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

作者： Gabriele Calzolari Vidya Sumathy Christoforos Kanellakis George Nikolakopoulos Department of Computer Science Electrical and Space Engineering Robotics and AI Group Luleå University of Technology Sweden

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

In this article, we propose a novel communication-based action space enhancement for the D-MARL exploration algorithm to improve the efficiency of mapping an unknown environment, represented by an occupancy grid map. In general, communication between autonomous systems is crucial when exploring large and unstructured environments. In such real-world scenarios, data transmission is limited and relies heavily on inter-agent proximity and the attributes of the autonomous platforms. In the proposed approach, each agent’s policy is optimized by utilizing the heterogeneous-agent proximal policy optimization algorithm to autonomously choose whether to communicate or explore the environment. To accomplish this, multiple novel reward functions are formulated by integrating inter-agent communication and exploration. The investigated approach aims to increase efficiency and robustness in the mapping process, minimize exploration overlap, and prevent agent collisions. The D-MARL policies trained on different reward functions have been compared to understand the effect of different reward terms on the collaborative attitude of the homogeneous agents. Finally, multiple simulation results are provided to prove the efficacy of the proposed scheme.

关键词： Autonomous systems Simulation Merging Employment Collaboration Reinforcement learning Robustness Data communication Optimization Intelligent robots

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Towards Collaborative Simultaneous Localization and Mapping: A Survey of the Current Research Landscape

Field Robotics

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Field robotics 2025年 2卷 971-1000页

作者： Pierre-Yves Lajoie Benjamin Ramtoula Fang Wu Giovanni Beltrame Department of Computer and Software Engineering Polytechnique Montréal Canada Oxford Robotics Institute Department of Engineering Science University of Oxford United Kingdom Desay SV Automotive Singapore

Motivated by the tremendous progress, we witnessed in recent years, this paper presents a survey of the scientific literature on the topic of Collaborative Simultaneous Localization and Mapping (C-SLAM), also known as multi-robot SLAM. With fleets of self-driving cars on the horizon and the rise of multi-robot systems in industrial applications, we believe that Collaborative SLAM will soon become a cornerstone of future robotic applications. In this survey, we introduce the basic concepts of C-SLAM and present a thorough literature review. We also outline the major challenges and limitations of C-SLAM in terms of robustness, communication, and resource management. We conclude by exploring the area's current trends and promising research avenues.

关键词： Robots Simultaneous localization and mapping Robot kinematics Robot sensing systems Collaboration Surveys Multi-robot systems Sensors Market research Trajectory

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Voxel Map to Occupancy Map Conversion Using Free Space Projection for Efficient Map Representation for Aerial and Ground Robots

arXiv

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arXiv 2024年

作者： Fredriksson, Scott Saradagi, Akshit Nikolakopoulos, George The Robotics and AI group The Department of Computer Science Electrical and Space Engineering Luleå University of Technology Sweden

This article introduces a novel method for converting 3D voxel maps, commonly utilized by robots for localization and navigation, into 2D occupancy maps for both unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs). The generated 2D maps can be used for more efficient global navigation for both UAVs and UGVs, in enabling algorithms developed for 2D maps to be useful in 3D applications, and allowing for faster transfer of maps between multiple agents in bandwidth-limited scenarios. The proposed method uses the free space representation in the UFOMap mapping solution to generate 2D occupancy maps. During the 3D to 2D map conversion, the method conducts safety checks and eliminates free spaces in the map with dimensions (in the height axis) lower than the robot’s safety margins. This ensures that an aerial or ground robot can navigate safely, relying primarily on the 2D map generated by the method. Additionally, the method extracts the height of navigable free space and a local estimate of the slope of the floor from the 3D voxel map. The height data is utilized in converting paths generated using the 2D map into paths in 3D space for both UAVs and UGVs. The slope data identifies areas too steep for a ground robot to traverse, marking them as occupied, thus enabling a more accurate representation of the terrain for ground robots. The effectiveness of the proposed method in enabling computationally efficient navigation for both aerial and ground robots is validated in two different environments, over both static maps and in online implementation in an exploration mission. The methods proposed within this article have been implemented in the popular robotics framework ROS and are open-sourced. The code is available at: https://***/LTURAI/Map-Conversion-3D-Voxel-Map-to-2D-Occupancy-Map. Copyright © 2024, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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On the Faithfulness of Vision Transformer Explanations

arXiv

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arXiv 2024年

作者： Wu, Junyi Kang, Weitai Tang, Hao Hong, Yuan Yan, Yan Department of Computer Science Illinois Institute of Technology United States Robotics Institute Carnegie Mellon University United States Department of Computer Science University of Connecticut United States

To interpret Vision Transformers, post-hoc explanations assign salience scores to input pixels, providing human-understandable heatmaps. However, whether these interpretations reflect true rationales behind the model’s output is still underexplored. To address this gap, we study the faithfulness criterion of explanations: the assigned salience scores should represent the influence of the corresponding input pixels on the model’s predictions. To evaluate faithfulness, we introduce Salience-guided Faithfulness Coefficient (SaCo), a novel evaluation metric leveraging essential information of salience distribution. Specifically, we conduct pair-wise comparisons among distinct pixel groups and then aggregate the differences in their salience scores, resulting in a coefficient that indicates the explanation’s degree of faithfulness. Our explorations reveal that current metrics struggle to differentiate between advanced explanation methods and Random Attribution, thereby failing to capture the faithfulness property. In contrast, our proposed SaCo offers a reliable faithfulness measurement, establishing a robust metric for interpretations. Furthermore, our SaCo demonstrates that the use of gradient and multilayer aggregation can markedly enhance the faithfulness of attention-based explanation, shedding light on potential paths for advancing Vision Transformer explainability. Copyright © 2024, The Authors. All rights reserved.

关键词： Distribution transformers

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Robotic Exploration through Semantic Topometric Mapping

Robotic Exploration through Semantic Topometric Mapping

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IEEE International Conference on robotics and Automation (ICRA)

作者： Scott Fredriksson Akshit Saradagi George Nikolakopoulos Department of Computer Science Robotics and AI Group Electrical and Space Engineering at Luleå University of Technology Sweden

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

In this article, we introduce a novel strategy for robotic exploration in unknown environments using a semantic topometric map. As it will be presented, the semantic topometric map is generated by segmenting the grid map of the currently explored parts of the environment into regions, such as intersections, pathways, dead-ends, and unexplored frontiers, which constitute the structural semantics of an environment. The proposed exploration strategy leverages metric information of the frontier, such as distance and angle to the frontier, similar to existing frameworks, with the key difference being the additional utilization of structural semantic information, such as properties of the intersections leading to frontiers. The algorithm for generating semantic topometric mapping utilized by the proposed method is lightweight, resulting in the method’s online execution being both rapid and computationally efficient. Moreover, the proposed framework can be applied to both structured and unstructured indoor and outdoor environments, which enhances the versatility of the proposed exploration algorithm. We validate our exploration strategy and demonstrate the utility of structural semantics in exploration in two complex indoor environments by utilizing a Turtlebot3 as the robotic agent. Compared to traditional frontier-based methods, our findings indicate that the proposed approach leads to faster exploration and requires less computation time.

关键词： Measurement Laser radar Navigation Semantics Skeleton Iron Indoor environment

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Global Solar Radiation Prediction using Empirical based Models 1

Global Solar Radiation Prediction using Empirical based Mode...

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1st International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2022

作者： Sivakumar, Mahima Priya, S. Jeba Subathra, M.S.P Karunya Institute of Technology and Sciences Department of Computer Science and Engineering Coimbatore India Karunya Institute of Technology and Sciences Department of Robotics Engineering Coimbatore India

ISBN: (纸本)9781665497107

Solar Radiation (SR) is crucial for the energy balance at the Earth's surface, evaporation, snow melting, plant water needs, and catchment hydrological regulation. In this regard, the major goal of this research is constructing a mathematical model or in other words empirical model to estimate the amount of SR upon a horizontal region in terms of latitude for four Indian cities. The cities considered for this work are NewDelhi, Chennai, Hyderabad and Coimbatore. Based on the input parameters, two categories of empirical models are developed namely, category 1 is sunshine duration (SD) based models and category 2 is air temperature (AT) based models. For performance evaluation, the metrics mean percentage error (MPE), mean bias error (MBE), mean absolute bias error (MABE), root mean square error (RMSE), mean absolute percentage error (MAPE) and coefficient of determination (R2). The results signify that both the category of empirical models have a promising capability in this field of research and can hence be an efficient option for solar forecasting. © 2022 IEEE.

关键词： Solar energy

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Enabling Reachability Across Multiple Domains Without Controller Synchronization in SDN

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computers, Materials & Continua 2021年第10期69卷 945-965页

作者： Nauman Khan Rosli Bin Salleh Ihsan Ali Zahid Khan Noman Mazhar Roobaea Alroobaea Fahad Almansour Usman Ali Department of Computer System and Technology Faculty of Computer Science and Information TechnologyUniversity of MalayaMalaysia Department of Computer Science and IT University of MalakandPakistan Robotics and Internet-of-Things Lab Prince Sultan UniversityRiyadhSaudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science College of Sciences and Arts RassQassim UniversityBuraydah51452Saudi Arabia

Software-defined networking(SDN)makes network agile and flexible due to its programmable *** extensive network has multiple domains in SDN for the scalability and performance of the ***,the inter-domain link is also crucial for the stability of the entire network on the data plane *** than one inter-domain connection enhances the scalability of the data plane ***,it faces a reachability problem with the principal root,which causes forwarding loops and packet drops in the network,thereby degrading network *** proposed solution is a multiple controller architecture;however,this approach increases the complexity and affects network ***,in this study,we propose a framework that avoids forwarding loops and packet drops without the synchronization of multiple-domain controllers in the network using an avoid loop with test packet ***,we collect the link status for improved routing and load balancing for the upcoming flow across inter-domain links to prevent congestion and increase throughput in real *** proposed methodology can significantly reduce the controller workload against multiple controller architecture,minimize flow setup latency,and improve throughput.

关键词： Multiple domain packet drop forwarding loop load balancing SDN multiple controller

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Body-aware Local Navigation for Asymmetric Holonomic Robots using Control Barrier Functions

Body-aware Local Navigation for Asymmetric Holonomic Robots ...

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European Control Conference (ECC)

作者： Akshit Saradagi Scott Fredriksson Anton Koval George Nikolakopoulos Department of Computer Science Electrical and Space Engineering Robotics and AI Group Luleå University of Technology Sweden

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

In this article, we propose a body-aware local navigation strategy for asymmetric holonomic robots for collision-free navigation in narrow pathways with sharp turns. In such scenarios, a robot with non-circular or asymmetric footprint that is comparable to the dimension of the pathways collides with walls when tracking Voronoi paths or risk-aware paths. This problem is addressed in this article through a novel multi-control barrier functions (CBF) based control strategy that achieves the objective of safe collision-free maneuvering at sharp turns. The proposed method is significantly computationally light in comparison to approaches based on model predictive control and online occupancy-grid based free-space and collision detection. In the proposed approach, a minimal set of parameters that characterize a sharp turn and the robot footprint are used to define six control barrier functions that define safe and unsafe regions of operation for a robot. A quadratic programming based CBF safety filter is designed that takes a nominal goal-reaching control as input and returns a minimally-deviating output that enforces the control barrier constraints and renders the safe set forward invariant throughout the turning maneuver. The three kinematic control inputs of the holonomic robot are shared in a conflict-free manner among the six control barrier constraints. The proposed local navigation approach was thoroughly validated in multiple scenarios in a simulated environment, where a robot with asymmetric footprint achieves collision-free maneuvering along multiple sharp turns, while respecting the safety and actuation constraints.

关键词： Laser radar Navigation Kinematics Turning Safety Quadratic programming Mobile robots

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Deep Image Clustering by Spiking Neural Networks

Deep Image Clustering by Spiking Neural Networks

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2023 IEEE Applied Imagery Pattern Recognition Workshop, AIPR 2023

作者： Mahyari, Arash Aliakbarpour, Hadi PensacolaFL United States University of West Florida Department of Intelligent Systems and Robotics PensacolaFL United States Saint Louis University Department of Computer Science St. LouisMO United States

ISBN: (纸本)9798350359527

Neuromorphic cameras, or event cameras, are biologically-inspired sensors that detect changes in illumination at a pixel level, different from traditional cameras where each pixel independently and asynchronously outputs when it senses illumination changes. The neuromorphic cameras exhibit high-Temporal resolution and dynamic range, useful in various applications. Spiking Neural Networks (SNNs), mimicking biological neurons, are efficient in processing neuromorphic images due to their event-driven, low-power nature. However, training SNNs is challenging because of the non-differentiability of neuron models which require different optimization techniques. Inspired by recent works on unsupervised deep clustering in conventional deep learning, we introduce a novel deep clustering algorithm that employs SNNs to extract and group visual features from neuromorphic images into clusters. It utilizes an SNN feature extractor for neuromorphic images, grouping the extracted features using K-means clustering. This algorithm, which doesn't require pre-Trained SNN weights, alternates between cluster updates and SNN weight adjustments. The extracted feature vectors in SNN are clustered and used as pseudo-labels for supervised training of the SNN extractor. The performance of the proposed algorithm is evaluated on two datasets of MNIST and NMNIST, and its effectiveness is assessed using the Normalized Mutual Information (NMI) metric. The performance of our SNN system with neuromorphic images, while marginally below its counterparts of ANNs with traditional images, demonstrates considerable potential. © 2023 IEEE.

关键词： Cameras

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