Autonomous robot navigation can be particularly demanding, especially when the surrounding environment is not known and safety of the robot is crucial. This work relates to the synthesis of control Barrier Functions (...
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ISBN:
(纸本)9798350377712;9798350377705
Autonomous robot navigation can be particularly demanding, especially when the surrounding environment is not known and safety of the robot is crucial. This work relates to the synthesis of control Barrier Functions (CBFs) through data for safe navigation in unknown environments. A novel methodology to jointly learn CBFs and corresponding safe controllers, in simulation, inspired by the State Dependent Riccati Equation (SDRE) is proposed. The CBF is used to obtain admissible commands from any nominal, possibly unsafe controller. An approach to apply the CBF inside a safety filter without the need for a consistent map or position estimate is developed. Subsequently, the resulting reactive safety filter is deployed on a multirotor platform integrating a LiDAR sensor both in simulation and real-world experiments.
The proceedings contain 61 papers. The special focus in this conference is on Complex, intelligent and Software Intensive systems. The topics include: In-advance replica arrangement of shared data over hybrid peer-to-...
ISBN:
(纸本)9783030504533
The proceedings contain 61 papers. The special focus in this conference is on Complex, intelligent and Software Intensive systems. The topics include: In-advance replica arrangement of shared data over hybrid peer-to-peer network according to users’ locations and preferences;a method of data augmentation for shunt murmur angiostenosis detection;study on visualization of characteristics of local government by open data and synesthesia in cross-cutting and systematic regional community networks;an event response fuzzy-based system for actor node selection in wsans;development of training system for dental treatment using webar and leap motion controller;impact of the interactive e-learning instructions on effectiveness of a programming course;an admission control system for 5g wireless networks considering fuzzy logic and software-defined network approaches;a fuzzy-based adiantum cultivation support system design;deploy, connect and execute scientific models;software-oriented routing protocol for energy-efficient wireless communications;control theoretical modeling of trust-based decision making in food-energy-water management;a prototype system of social experiment for actual road state information platform based on sensors and v2x communication;an autonomous wireless platform for the remote inspection of pollutants;quadcoins-network: a deep learning approach to sound source localization;green fog: cost efficient real time power management service for green community;extractive summarization by rouge score regression based on bert;a development framework for rp-type serious games in a 3d virtual environment;sound source separation based on multichannel non-negative matrix factorization with weighted averaging;intelligentbox based training system for operation of radiation therapy devices;android malware detection using multi-stage classification models.
The Internet of Things (IoTs) refers to the interconnection of commonplace objects such as smartphones, Internet TVs, sensors, and actuators with the Internet. This interconnection facilitates intelligent communicatio...
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Quadrupedal robots excel in mobility, navigating complex terrains with agility. However, their complex controlsystems present challenges that are still far from being fully addressed. In this paper, we introduce the ...
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ISBN:
(纸本)9798350377712;9798350377705
Quadrupedal robots excel in mobility, navigating complex terrains with agility. However, their complex controlsystems present challenges that are still far from being fully addressed. In this paper, we introduce the use of Sample-Based Stochastic control strategies for quadrupedal robots, as an alternative to traditional optimal control laws. We show that Sample-Based Stochastic methods, supported by GPU acceleration, can be effectively applied to real quadruped robots. In particular, in this work, we focus on achieving gait frequency adaptation, a notable challenge in quadrupedal locomotion for gradient-based methods. To validate the effectiveness of Sample-Based Stochastic controllers we test two distinct approaches for quadrupedal robots and compare them against a conventional gradient-based Model Predictive control system. Our findings, validated both in simulation and on a real 21Kg Aliengo quadruped, demonstrate that our method is on par with a traditional Model Predictive control strategy when the robot is subject to zero or moderate disturbance, while it surpasses gradient-based methods in handling sustained external disturbances, thanks to the straightforward gait adaptation strategy that is possible to achieve within their formulation.
Quadcopter UAV relies on flexible and free maneuverability and strong expandability, which makes its application scenes more and more abundant. At present, the application of quadcopter UAVs in target detection, real-...
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Efficiently learning strategic multi-agent behavior remains a challenge for robotic systems deployed in real-world scenarios, especially when considering underactuated or dynamically unstable systems. Such systems dem...
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ISBN:
(纸本)9798350377712;9798350377705
Efficiently learning strategic multi-agent behavior remains a challenge for robotic systems deployed in real-world scenarios, especially when considering underactuated or dynamically unstable systems. Such systems demand an integrated approach that informs long-term strategic planning with constraints imposed by reactive control, and vice versa, to effectively accomplish task objectives in competitive scenarios. In this paper, we introduce a hierarchical control model to address this: a high-level controller synthesizes strategic guidance from aggregated team experiences, while a low-level controller formulates corresponding task-specific continuous controls. We apply this concept to coordination of competitive multi-team behavior in dynamic flight scenarios with F-16 aircraft. This work introduces a hierarchical reinforcement learning approach for multi-agent coordination, leveraging decoupled distributional value representations at the high-level together with goal-conditioned policy learning at the low-level, providing a control structure that integrates long-horizon strategic planning with short-horizon dynamic control. We further provide a parallel simulator for efficient learning with multi-agent F-16 dynamics.
With the use of sophisticated movement monitoring, computer vision, and artificial intelligence algorithms, gesture controlsystems transform interactions in environments that pose a threat to human safety. These solu...
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We study different approaches to use real-time communication between vehicles, in order to improve and to optimize traffic flow in the future. A leading example in this contribution is a virtual version of the promine...
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ISBN:
(纸本)9789897586521
We study different approaches to use real-time communication between vehicles, in order to improve and to optimize traffic flow in the future. A leading example in this contribution is a virtual version of the prominent ring road experiment in which realistic, human-like driving generates stop-and-go waves. To simulate human driving behavior, we consider microscopic traffic models in which single cars and their longitudinal dynamics are modeled via coupled systems of ordinary differential equations. Whereas most cars are set up to behave like human drivers, we assume that one car has an additional intelligentcontroller that obtains real-time information from other vehicles. Based on this example, we analyze different control methods including a nonlinear model predictive control (MPC) approach with the overall goal to improve traffic flow for all vehicles in the considered system. We show that this nonlinear controller may outperform other control approaches for the ring road scenario but intensive computational effort may prevent it from being real-time capable. We therefore propose an imitation learning approach to substitute the MPC controller. Numerical results show that, with this approach, we maintain the high performance of the nonlinear MPC controller, even in set-ups that differ from the original training scenarios, and also drastically reduce the computing time for online application.
This paper presents a model-based control strategy for usage in multilevel pressure boosting systems with centrifugal pumps operating in parallel. The control is based on a nonlinear system model using exact input-out...
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ISBN:
(纸本)9798350364309;9798350364293
This paper presents a model-based control strategy for usage in multilevel pressure boosting systems with centrifugal pumps operating in parallel. The control is based on a nonlinear system model using exact input-output linearization. With the help of an optimization algorithm, the total consumption flow rate is distributed optimally in such a way that the total hydraulic efficiency of all running pumps is maximized in steady state while complying with all constraints. Trajectories for every single pump are planned on model-based relations in order to reduce overshoots in the pipeline pressure, in particular during start-up processes. The whole control strategy is validated on a test bench.
6G networks, characterized by ultra-low latency and ubiquitous computing, herald a new era where Connected and Autonomous Electric Vehicles (CAEVs) and Unmanned Aerial Vehicles (UAVs) are redefining smart mobility. Eq...
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ISBN:
(纸本)9798350390148;9798350390131
6G networks, characterized by ultra-low latency and ubiquitous computing, herald a new era where Connected and Autonomous Electric Vehicles (CAEVs) and Unmanned Aerial Vehicles (UAVs) are redefining smart mobility. Equipped with real-time data processing, Artificial Intelligence (AI), and seamless connectivity, these vehicles seek efficient charging solutions facilitated by intelligent Edge computing (IEC). IEC, through latency reduction and optimized charging processes, promises rapid charging, grid stability, enhanced security, and renewable energy integration for intelligent transportation systems (ITS). This survey comprehensively examines IEC techniques and architectures, uncovering their impact on charging efficiency, security, and reliability within smart mobility frameworks. Through a review of research papers, the survey provides insights into real-world applications and IEC advancements, revealing key challenges and emerging research directions. The survey envisions an efficient, secure, and interconnected 6G-era charging ecosystem, with future directions including ultra-fast charging, renewables integration, enhanced security, standardization, AV- V2X synergy, predictive maintenance, and blockchain transparency, fundamentally reshaping AI-driven smart mobility.
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