The digital revolution has opened numerous new possibilities for controlsystems solutions with potential for widespread societal impacts. Thus, it is important to explore how the design of controlsystems can be perf...
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The digital revolution has opened numerous new possibilities for controlsystems solutions with potential for widespread societal impacts. Thus, it is important to explore how the design of controlsystems can be performed in such a manner that these impacts can be steered towards contributing to the achievement of the United Nations Sustainable Development Goals (UN SDGs). The IFAC Technical Committee 9.2, systems and control for Societal Impact, is deeply interested in maximizing the benefits of automation, controland intelligent systems for society while avoiding their possible negative effects by anticipating potential adverse effects. The TC 9.2 is building its vision and activities along the emerging new field of cyber-physical-human systems (CPHS). This field is growing due to the proliferation of interactions between humans and (embedded, networked, interconnected) cyber-physical systems (CPS). The interplay between humans and CPS leads to new societal impacts and requires new tools for directing and guiding these impacts. Moreover, such interactions in CPHS require interdisciplinary collaborations between engineers and social and behavioral scientists and humanists for achieving the responsible development of CPHS. In this paper, we recap TC9.2 topics and visions. We discuss the responsible development of CPHS which is the driving goal of the TC9.2 committee. We initiate an analysis to relate TC 9.2 topics with UN SDGs, through the idea of "six transformations". The importance of stages of research development driven by SDG goals as well as the importance of individuals, corporations, and governments in this responsible design of systems is also highlighted. The close relation of the TC 9.2 visions with Digital Revolution for Sustainable Development through CPHS is discussed in detail. Relations with other transformations are also studied. Copyright (C) 2024 The Authors.
intelligentautomation has revolutionized logistics operations, especially warehouse management. This study provides an in-depth investigation into improving inventory management through the use of artificial intellig...
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Accurate state estimation plays a critical role in ensuring the robust control of humanoid robots, particularly in the context of learning-based control policies for legged robots. However, there is a notable gap in a...
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ISBN:
(纸本)9798350377712;9798350377705
Accurate state estimation plays a critical role in ensuring the robust control of humanoid robots, particularly in the context of learning-based control policies for legged robots. However, there is a notable gap in analytical research concerning estimations. Therefore, we endeavor to further understand how various types of estimations influence the decision-making processes of policies. In this paper, we provide quantitative insight into the effectiveness of learned state estimations, employing saliency analysis to identify key estimation variables and optimize their combination for humanoid locomotion tasks. Evaluations assessing tracking precision and robustness are conducted on comparative groups of policies with varying estimation combinations in both simulated and real-world environments. Results validated that the proposed policy is capable of crossing the sim-to-real gap and demonstrating superior performance relative to alternative policy configurations.
Active reconstruction technique enables robots to autonomously collect scene data for full coverage, relieving users from tedious and time-consuming data capturing process. However, designed based on unsuitable scene ...
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ISBN:
(纸本)9798350377712;9798350377705
Active reconstruction technique enables robots to autonomously collect scene data for full coverage, relieving users from tedious and time-consuming data capturing process. However, designed based on unsuitable scene representations, existing methods show unrealistic reconstruction results or the inability of online quality evaluation. Due to the recent advancements in explicit radiance field technology, online active high-fidelity reconstruction has become achievable. In this paper, we propose GS-Planner, a planning framework for active high-fidelity reconstruction using 3D Gaussian Splatting. With improvement on 3DGS to recognize unobserved regions, we evaluate the reconstruction quality and completeness of 3DGS map online to guide the robot. Then we design a sampling-based active reconstruction strategy to explore the unobserved areas and improve the reconstruction geometric and textural quality. To establish a complete robot active reconstruction system, we choose quadrotor as the robotic platform for its high agility. Then we devise a safety constraint with 3DGS to generate executable trajectories for quadrotor navigation in the 3DGS map. To validate the effectiveness of our method, we conduct extensive experiments and ablation studies in highly realistic simulation scenes.
In Industry 4.0, achieving semantic interoperability is a significant problem due to the complexities of current automationsystems and the numerous standards involved. The study explores how Artificial Intelligence (...
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ISBN:
(纸本)9798350361261;9798350361278
In Industry 4.0, achieving semantic interoperability is a significant problem due to the complexities of current automationsystems and the numerous standards involved. The study explores how Artificial Intelligence (AI) and semantic interoperability connect within the Internet of Things (IoT) framework to overcome barriers to technology adoption. The main goal is to analyze how AI's adaptive and predictive abilities might transform semantic interoperability by studying AI-driven methodologies to provide a flexible and efficient solution. The main objective of the paper is to leverage Named Entity Recognition (NER) AI models to streamline the identification of entities within the Internet of Things (IoT) for achieving semantic interoperability. It tests a Natural Language Processing (NLP) translator on data representations not seen during training, and the outcome highlights the efficiency of NLP in correctly understanding and processing these representations.
We present and evaluate a novel suction-based gripper designed for fruit picking. This work is motivated by common problems observed in field trials of robotic harvesting: Calibration/perception errors, workspace obst...
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ISBN:
(纸本)9798350384581;9798350384574
We present and evaluate a novel suction-based gripper designed for fruit picking. This work is motivated by common problems observed in field trials of robotic harvesting: Calibration/perception errors, workspace obstacles, fruit swinging/moving when contacted, and varying stem and branch stiffnesses. The gripper consists of three suction-cups located on the palm, along with in-hand perception. To evaluate the gripper, we developed a physical proxy that approximates a realistic apple-stem-branch dynamic system. We performed 756 apple picks on the proxy with varying branch stiffness, stem strength and gripper pose (yaw, roll and offset w.r.t. the apple). Our results show that grasping performance improves when the gripper yaw w.r.t. the apple has two suction cups on the bottom of the apple and one suction cup on top. Even with +/- 15mm offset, at least two suction cups engaged with the apple 80% of the time, regardless of branch stiffness. Moreover, the gripper withstands +/- 20mm offset when it approaches the apple near its equator.
The Capacitated Vehicle Routing Problem with Time Windows (CVRPTW) is a representative model for multi-UGVs task planning. It describes the allocation for tasks of several unmanned vehicles, considering the capacity o...
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ISBN:
(纸本)9798350354416;9798350354409
The Capacitated Vehicle Routing Problem with Time Windows (CVRPTW) is a representative model for multi-UGVs task planning. It describes the allocation for tasks of several unmanned vehicles, considering the capacity of each vehicle and the requirements, as well as the time windows, of various tasks. However, existing studies primarily focus on the task assignment and do not consider the connection between path costs and obstacles in complicated scenarios. In this paper, we propose a coupled task and path planning algorithm for multiple unmanned vehicles under environmental inspiration. We introduces a novel path cost function and achieve seamless integration of solutions from the task level to the path level. Experimental results indicate that, in static obstacle environments, our algorithm module can provide more accurate task assignment and path planning results with smaller costs under similar time consumption.
cyber-physical systems (CPSs) are on the rise for safety-critical applications. While formal verification approaches may work on simple systems, these approaches need more scalability. When systems are sufficiently co...
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ISBN:
(纸本)9798350384529;9798350384512
cyber-physical systems (CPSs) are on the rise for safety-critical applications. While formal verification approaches may work on simple systems, these approaches need more scalability. When systems are sufficiently complex, testing is often the only practical way to gain confidence the system works as expected. How can we generate high-quality tests for CPS? This work proposes an approach to improve test case generation for CPSs. We achieve this by proposing a new model-based seed generation algorithm in the fuzz testing pipeline. We first use the Koopman operator technique to construct a predictor model to capture the effect of time-varying inputs on the CPS behavior. Then, we use the model in a Model Predictive control (MPC) optimization loop, generating control inputs that drive the system through state space. We evaluate the strategy's effectiveness through extensive experiments on the well-known neural network air-to-air collision avoidance benchmark, ACAS Xu. Evaluation results prove that the proposed Koopman MPC approach achieves better test coverage than other fuzz testing and falsification tools.
In this paper, we propose an adaptive tracking control scheme for nonlinear satellite systems with dynamic uncertainty and unknown actuator failures. A fixed-time adaptive fault-tolerant control scheme is designed by ...
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The use of fifth-generation (5G) cellular networks is growing in industrial applications such as factory automationsystems. 5G networks provide two essential services: Enhanced Mobile Broadband (eMBB) and Ultra-Relia...
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ISBN:
(纸本)9798350309461
The use of fifth-generation (5G) cellular networks is growing in industrial applications such as factory automationsystems. 5G networks provide two essential services: Enhanced Mobile Broadband (eMBB) and Ultra-Reliable Low-Latency Communication (URLLC). eMBB services require high data rates with some lower limits, while URLLC traffic has strict latency and reliability requirements. Previous methods for scheduling eMBB and URLLC traffic have assumed that URLLC traffic always preempts eMBB traffic upon arrival, which can negatively affect the achievable eMBB data rates. Additionally, prior work has not considered ensuring minimum data rate requirements for certain eMBB traffic. This paper proposes a novel framework for network resource allocation for coexisting eMBB and URLLC traffic. The proposed framework uses a hybrid offline/online approach to ensure that the Quality of Service (QoS) requirements for eMBB and URLLC traffic are met. Our framework can meet the latency and reliability requirements of URLLC traffic while maximizing data rates for eMBB traffic in a fair way and fulfilling their minimum data rate requirements. Experimental results show that our proposed framework is more effective than the current state-of-the-art methods.
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