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检索条件"任意字段=Conference on Next-Generation Robots and Systems"

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Internet of Robotic Things: Current Technologies and Applications 22

Internet of Robotic Things: Current Technologies and Applica...

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22nd International Arab conference on Information Technology (ACIT)

作者： Samara, Ghassan Hussein, Abla Matarneh, Israa Abdullah Alrefai, Mohammed Al-Safarini, Maram Y. Zarqa Univ Comp Sci Dept Zarqa Jordan Zarqa Univ Software Engn Dept Zarqa Jordan

ISBN: (纸本)9781665419956

The Internet of Robotic Things (IoRT) is a new domain that aims to link the IoT environment with robotic systems and technologies. IoRT connects robotic systems, connects them to the cloud, and transfers critical information as well as knowledge exchange to conduct complicated and intricate activities that a human cannot readily perform. The pertinent notion of IoRT has been discussed in this paper, along with the issues that this area faces on a daily basis. Furthermore, technological applications have been examined in order to provide a better understanding of IoRT and its current development phenomenon. The study describes three layers of IoRT infrastructure: network and control, physical, and service and application layer. In the next section, IoRT problems have been presented, with a focus on data processing and the security and safety of IoRT technological systems. In addition to discussing the difficulties, appropriate solutions have been offered and recommended. IoRT is regarded as an essential technology with the ability to bring about a plethora of benefits in smart society upon adoption, contributing to the generation and development of smart cities and industries in the near future.

关键词： Internet of Robotic Things IoRT Data Processing Security and Safety IoT Cloud robots

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UAV-as-a-Service for Robotic Edge System Resilience

UAV-as-a-Service for Robotic Edge System Resilience

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IEEE International conference on Web Services (ICWS)

作者： Shi Li Jiong Jin Mahbuba Afrin Qiushi Zheng Jing Fu Yu-Chu Tian School of Science Computing and Engineering Technologies Swinburne University of Technology Melbourne Australia School of Electrical Engineering Computing and Mathematical Sciences Curtin University Perth Australia School of Engineering STEM College RMIT University Melbourne Australia School of Computer Science Queensland University of Technology Brisbane Australia

ISBN: (数字)9798350368550

ISBN: (纸本)9798350368567

By melding the capabilities of robotics with the agility of edge computing, Robotic Edge System (RES) exemplifies the next generation of Internet Intelligent Service systems, delivering incredible efficiency and adaptability across diverse real world applications. Inevitably, RES is susceptible to mechanical disruptions of robots, particularly when some tasks are assigned to faulty ones, leading to uncertain failures and performance degradation. Due to communication and latency constraints, it is not always feasible to rely on edge/cloud computing infrastructure for system recovery. To address these issues, a UAV-as-a-Service (UAVaaS) approach is proposed that leverages the mobility of UAVs to enhance system resilience. Specifically, a Markov Decision Process (MDP) is utilized to assign tasks dynamically among active UAVs to achieve system recovery in a livestock monitoring scenario. Additionally, a Dual Noise Deep Deterministic Policy Gradient (DNDDPG)-based mechanism is proposed to minimize system recovery time and energy consumption. The proposed DNDDPG enhances exploration and decision-making during training by integrating parameter noise and behavioral noise into the classic Deep Deterministic Policy Gradient (DDPG) algorithm. The simulation results indicate that the proposed mechanism can achieve convergence within 100 episodes, thereby effectively minimizing the time and energy required for system recovery.

关键词： Fault tolerance Energy consumption Web services Noise Decision making System recovery Livestock robots Monitoring Convergence

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Autonomous Versus Manual Control of a Pasture Sanitation Robot 12th

Autonomous Versus Manual Control of a Pasture Sanitation R...

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Proceedings of the 12th International conference on Biomimetic and Biohybrid systems, Living Machines 2023

作者： Adams, Ian Quinn, Roger Lee, Greg Kroeger, Alexandra Feuerbacher, Erica N. Department of Mechanical and Aerospace Engineering Case Western Reserve University ClevelandOH44106-7222 United States Department of Electrical Engineering and Computer Science Case Western Reserve University ClevelandOH44106-7222 United States Department of Animal and Poultry Science Virginia Tech BlacksburgVA24061 United States

ISBN: (纸本)9783031395031

This work presents the collection and analysis of data from animal-robot interactions in two different control schemes. Cows (B. taurus) and horses (E. caballus) were introduced in pasture to a robot controlled either manually via teleoperation and autonomously via a costmap-based navigation algorithm. The robot maneuver at random, simulating a manure collection task, until all animals in the pasture lost vigilant attention to the robot. The time of initial loss of interest, interest over time, and time of ultimate loss of interest (10 consecutive seconds of non-vigilance) were recorded. The pasture sanitation robot was successful in manual and autonomous navigation of pastures. The robot was able to operate autonomously in pasture safely without changing qualitative response from the animals, as compared to manual methods. The deployment of autonomous control did not increase stress as a function of vigilance as compared to manual teleoperation. Both methods contribute to the development and evaluation of future pasture sanitation robots. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： robots

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A Phase-Change Emulsion Jamming Gripper for Manipulation of Micro-Scale Textured Surfaces

A Phase-Change Emulsion Jamming Gripper for Manipulation of ...

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IEEE International conference on Robotics and Automation (ICRA)

作者： Alex Keller Tianqi Yue Qiukai Qi Andrew T. Conn Jonathan Rossiter School of Engineering Mathematics and Technology and the Bristol Robotics Laboratory University of Bristol Bristol UK

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

The inherent elasticity of soft materials can be used to create robotic grippers that deform and comply to a variety of irregular shapes. To date, several soft adaptive grasping strategies have been reported, however, most of them focus on adapting to the overall shape of the structure, while the adaptive grasping of small surface asperities is overlooked. In this paper, we propose a novel method to achieve adaptive grasping on surface asperities with a smart shape-memory silicone sponge. Heating above 60°C makes the sponge soft and deformable to allow it to penetrate within surface asperities via a pressure normal to the surface. Cooling down below 60°C makes the sponge "jam" to retain its deformed shape. The interlocking force between the jammed sponge and the asperities, and the increased area of contact, allows for adaptive grasping on asperities down to 0.4 mm with an adhesive force of up to 27.7 N in a 40 × 40 mm contacting area. We introduce the design, working principle, fabrication, and optimization of a robotic gripper based on this shape-memory silicone sponge. This sponge-jamming gripper shows great potential for developing next-generation robotic grippers for the manipulation of textured and discontinuous surfaces.

关键词： Shape Service robots Force Grasping Pneumatic systems Surface texture Grippers

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Neuromorphic-Driven Agentic AI for Autonomous Decision-Making systems

Neuromorphic-Driven Agentic AI for Autonomous Decision-Makin...

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Mobile Networks and Wireless Communications (ICMNWC), IEEE International conference on

作者： Manjunath Kamath K Samata Mehta.S Akshaya H. L Shilpashree N Girish Jadhav Abhijit Mitra Department of Cyber Security NMAM Institute of Technology NITTE (Deemed to be University) Karkala India Department Of CSE (IOT & Cyber Security including Block Chain Technology) Brindavan College of Engineering Bengaluru India Department of Computer Science Sarada Vilas College Mysuru India Department Of Electrical Engineering Faculty of Engineering and Technology Parul institute of Engineering and Technology Parul University Post Limda India Symbiosis Centre for Advanced Legal Studies and Research (SCALSAR) Symbiosis Law School Symbiosis International (Deemed University) Pune India

ISBN: (数字)9798331528348

ISBN: (纸本)9798331528355

Agentic AI represents a paradigm shift in the development of intelligent systems capable of adaptive and proactive interactions in dynamic and complex environments. By integrating reinforcement learning (RL) with cognitive frameworks, Agentic AI goes beyond traditional rule-based and reactive models, enabling autonomous systems to make informed decisions, anticipate future states, and learn from experience. This paper explores the theoretical foundations and practical applications of Agentic AI, highlighting its potential to transform a variety of fields, including robotics, autonomous driving, finance, and healthcare. Through a detailed review of state-of-the-art research, we illustrate how cognitive architectures such as ACT-R and Soar, combined with advanced RL techniques like Deep Q-Networks (DQN) and Proximal Policy Optimization (PPO), contribute to the development of AI agents with human-like reasoning and decision-making capabilities. Experimental results demonstrate that Agentic AI significantly outperforms conventional AI approaches in terms of adaptability, learning efficiency, and decision accuracy. The findings suggest that Agentic AI offers a robust framework for creating intelligent systems capable of complex problem-solving, long-term planning, and proactive behavior, paving the way for the next generation of AI-driven applications.

关键词： Adaptation models Adaptive systems Decision making Finance Medical services Reinforcement learning Cognition Autonomous vehicles robots Optimization

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Blockchain Forum, the Robotic Process Automation (RPA) Forum, and the Central and Eastern Europe (CEE) Forum, held as part of the 20th International conference on Business Process Management, BPM 2022

Blockchain Forum, the Robotic Process Automation (RPA) Forum...

引用

Blockchain Forum, the Robotic Process Automation (RPA) Forum, and the Central and Eastern Europe (CEE) Forum, held as part of the 20th International conference on Business Process Management, BPM 2022

ISBN: (纸本)9783031161674

The proceedings contain 21 papers. The special focus in this conference is on Blockchain. The topics include: Rolling Back to Manual Work: An Exploratory Research on Robotic Process Re-Manualization;Steering the robots: An Investigation of IT Governance Models for Lightweight IT and Robotic Process Automation;Identifying the Socio-Human Inputs and Implications in Robotic Process Automation (RPA): A Systematic Mapping Study;a Human-in-the-Loop Approach to Support the Segments Compliance Analysis;recommending next Best Skill in Conversational Robotic Process Automation;Process Discovery Analysis for Generating RPA Flowcharts;can You Teach Robotic Process Automation Bots New Tricks?;API as Method for Improving Robotic Process Automation;Business Process Management in CEE Countries: A Literature-Based Research Landscape;process and Project Oriented Organization: The Essence and Maturity Measurement;Pupa: Smart Contracts for BPMN with Time-Dependent Events and Inclusive Gateways;the Competencies for Knowledge Management and the Process Orientation in the Post-Covid Economy. generation Z Students Perspective;The Future Development of ERP: Towards Process ERP systems?;a Systematic Local Fork Management Framework for Blockchain Sandbox Environments;fine-Grained Data Access Control for Collaborative Process Execution on Blockchain;challenges and Opportunities of Blockchain for Auditable Processes in the Healthcare Sector;measuring the Effects of Confidants on Privacy in Smart Contracts;threshold Signature for Privacy-Preserving Blockchain;from Natural Language to Workflows: Towards Emergent Intelligence in Robotic Process Automation.

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M2SN: Adaptive and Dynamic Multi-modal Shortcut Network Architecture for Latency-Aware Applications

M2SN: Adaptive and Dynamic Multi-modal Shortcut Network Arch...

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IEEE International conference on Multimedia and Expo (ICME)

作者： Yifei Pu Chi Wang Xiaofeng Hou Cheng Xu Jiacheng Liu Jing Wang Minyi Guo Chao Li Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Computer Science and Engineering Chinese University of Hong Kong Hong Kong China

ISBN: (数字)9798350390155

ISBN: (纸本)9798350390162

Multi-modal neural networks have demonstrated exceptional performance by merging information across modalities, surpassing the state-of-the-art uni-modal DNNs. However, this accuracy improvement comes at the cost of increased computation, leading to higher inference latency. This defect significantly limits the practical value of multi-modal DNNs, especially for latency-aware applications. Therefore, we propose an adaptive and efficient multi-modal shortcut architecture called M 2 SN to reduce the execution latency with accuracy guarantees. It skips ineffective network layers to reduce computational costs as well as alleviate the overfitting problem adaptive to specific models and scenarios. The key contributions of M 2 SN are twofold: 1) We design and insert shortcuts into each uni-modal network to perform adaptive computing. 2) We design a navigator to dynamically choose the optimal shortcuts. Unlike previous approaches, M 2 SN features high generality as it does not rely on any prior knowledge. The experimental results show that M 2 SN can reduce 28.3% average latency while obtaining the same or higher accuracy compared with SOTA baselines.

关键词： Accuracy Adaptive systems Navigation Neural networks Merging Computer architecture Network architecture Explosions robots next generation networking

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Robot Dynamic Path Planning Based on the Fusion of Jump Point Search Algorithm and Dynamic Window Approach

Robot Dynamic Path Planning Based on the Fusion of Jump Poin...

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International conference on Advanced Robotics and Mechatronics (ICARM)

作者： Weijing Wang Xiangrong Xu Haining Miao Huanhuan Cui Aleksandar Rodić Petar B. Petrovic Shanshan Xu Haiyan Wang School of Computer Science and Technology Anhui University of Technology Ma’anshan Anhui China School of Mechanical Engineering Anhui University of Technology Ma’anshan Anhui China Faculty of Mechanical Engineering University of Belgrade Belgrade Serbia School of Osaka Medical Engineering Ma’anshan University Ma’anshan Anhui China

ISBN: (数字)9798350385724

ISBN: (纸本)9798350385731

To address the problem of slow route computation caused by excessive exploration of unnecessary nodes in traditional A* algorithm combined with the dynamic window approach, as well as the challenge of effectively leveraging global planning data for local navigation, this paper proposes an integrated method that combines the jump point search (JPS) algorithm with the dynamic window approach (DWA). First, the JPS algorithm is utilized in a pre-defined map environment for global route generation. next, a three-stage spline optimization is applied to improve the continuity and flow of the computed path. Finally, the optimized path nodes are selected and used as intermediate waypoints for the dynamic window approach to facilitate efficient local navigation. During the motion, these nodes guide the dynamic window approach algorithm in stages, aligning it more closely with the global planning path and allowing real-time avoidance of dynamic and static obstacles in the environment. Experimental results demonstrate that the fusion algorithm exhibits superior path planning capabilities, achieving global optimality and effective obstacle avoidance.

关键词： Navigation Heuristic algorithms Dynamics Search problems Path planning Real-time systems Planning Mobile robots Splines (mathematics) Optimization

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NSP: A Neuro-Symbolic Natural Language Navigational Planner

NSP: A Neuro-Symbolic Natural Language Navigational Planner

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International conference on Machine Learning and Applications (ICMLA)

作者： William English Dominic Simon Sumit Kumar Jha Rickard Ewetz ECE University of Florida Gainesville Florida USA Computer Science Department Florida International University Miami Florida USA

ISBN: (数字)9798350374889

ISBN: (纸本)9798350374896

Path planners that can interpret free-form natural language instructions hold promise to automate a wide range of robotics applications. These planners simplify user interactions and enable intuitive control over complex semi-autonomous systems. While existing symbolic approaches offer guarantees on the correctness and efficiency, they struggle to parse free-form natural language inputs. Conversely, neural approaches based on pre-trained Large Language Models (LLMs) can manage natural language inputs but lack performance guaran-tees. In this paper, we propose a neuro-symbolic framework for path planning from natural language inputs called NSP. The framework leverages the neural reasoning abilities of LLMs to i) craft symbolic representations of the environment and ii) a symbolic path planning algorithm. next, a solution to the path planning problem is obtained by executing the algorithm on the environment representation. The framework uses a feedback loop from the symbolic execution environment to the neural generation process to self-correct syntax errors and satisfy execution time constraints. We evaluate our neuro-symbolic approach using a benchmark suite with 1500 path-planning problems. The experimental evaluation shows that our neuro-symbolic approach produces 90.1% valid paths that are on average 19-77% shorter than state-of-the-art neural approaches.

关键词： Feedback loop Navigation Natural languages Syntactics Programming Path planning Planning Time factors robots Python

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Police Office Model Performance and Security Evaluation in a Simulated Group of Mobile robots 5

Police Office Model Performance and Security Evaluation in a...

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5th International conference on Future Networks and Distributed systems: The Premier conference on Smart next generation Networking Technologies, ICFNDS 2021

作者： Chuprov, Sergey Gataullin, Ruslan Neverov, Evgenii Belyaev, Pavel Kim, Iuliia Viksnin, Ilia Leti University Saint Petersburg Russia Itmo University Saint Petersburg Russia

ISBN: (纸本)9781450387347

In this paper, we implement and evaluate the performance and security of Police Office Model in a simulated mobile robotic system. The model was originally proposed for computer networks, however it has its potential performance and security advantages for cyber-physical systems, which was stated in earlier works. The details of the model adaptation to a group of mobile robotic devices are discussed. In our study, we follow multi-agent approach, which allows to represent system as a set of different distributed agents. To evaluate the Police Office Model adaptation effect, we conduct an empirical study using custom software simulation environment. As performance metrics, the time to perform task assigned to the agents, and the number of tasks performed over one iteration were used. During the simulation, some agents were malicious - i.e. provided incorrect data in the agents' intercommunication. The empirical study results demonstrated that Police Office Model implementation allows to increase both metrics in all simulated mobile robotic systems scenarios. on of the documentation of their work. © 2021 ACM.

关键词： Law enforcement

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