The proceedings contain 53 papers. The special focus in this conference is on intelligentcomputing in control and Communication. The topics include: A Comparative Study of Unit Commitment Problem by Dynamic Programmi...
ISBN:
(纸本)9789811584381
The proceedings contain 53 papers. The special focus in this conference is on intelligentcomputing in control and Communication. The topics include: A Comparative Study of Unit Commitment Problem by Dynamic Programming and Genetic Algorithm;Robust Fuzzy Logic controller for DC Motor Stability Enhancement Under Load Disturbances;optimal Scheduling for Delay Management in Railway Network Using Hybrid Bat Algorithm;optimal Rescheduling of Real Power to Mitigate Congestion Using Elephant Herd Optimization;preface;A Fuzzy-Based STATCOM controller for Grid Interconnection of Fuel System to Improve Power Quality;adiabatic Logic-Based Area- and Energy-Efficient Full Adder Design;Comparative Analysis of Rapid Single Flux Quantum (RSFQ) Circuit Technique Multipliers;techno-Economic Material Demand-Based Model in Plastic Waste Management Using Metaheuristic Algorithms;breaking Down and Reduplication of Information in Cloud for Best Overall Performance and Protection;A Novel Modulating PID controller for a Speed control of BLDC Motor Adopting Flower Pollination Algorithm;shaped Beams from Circular Aperture Antennas;A Simple and Low-Cost HIL Solution for control of Power Electronic Converters;improved Harmonic Profile of Multilevel Inverter Topology with Shifted Carrier Modulation Technique;artificial Intelligence Based control Methods for Speed control of Wind Turbine Energy System;recent Trends and Challenges in Blockchain Technology;Comparison of Uplink Spectral Efficiency in Massive MIMO systems;a Study on Static Call Admission control Policies for Wireless Mobile Cellular Networks;Design of Low PDP Ternary Circuits Utilizing Carbon Nanotube Field-Effect Transistors;Detection and Estimation of Multiple Point Targets for LFM Echo Using Compressed Sensing;Design of Dumbbell-Shaped MIMO Antenna for Wearable Applications.
Effectively modeling the spatio-temporal interactions both internally and externally is a challenge in controlling multi-linked snake robots. This paper presents an effective method based on deep predictive coding: Sn...
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ISBN:
(纸本)9798350377712;9798350377705
Effectively modeling the spatio-temporal interactions both internally and externally is a challenge in controlling multi-linked snake robots. This paper presents an effective method based on deep predictive coding: SnakeFormer, to address the aforementioned issue. The main contributions include: 1) Deriving a variational free energy function with two innovative regularization terms through Bayesian probabilistic analysis, offering a novel perspective to simulate the interactions between agent and the environment;2) Introducing an interaction-attention model within a Transformer structure for predicting dynamics, and collaboratively addressing path planning and obstacle avoidance tasks. 3) By incorporating serpenoid embedding and optimizing self-attention computations, the gait stability and motion efficiency are improved. Preliminary experiments and comparative analysis with baseline models fully validate the effectiveness and generalizability of the method.
Non-contact particle cluster manipulation holds significant promise in the realms of advanced manufacturing, chemistry, and pharmacy. However, achieving precise and dynamic control over the spatial kinematics of parti...
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ISBN:
(纸本)9798350377712;9798350377705
Non-contact particle cluster manipulation holds significant promise in the realms of advanced manufacturing, chemistry, and pharmacy. However, achieving precise and dynamic control over the spatial kinematics of particle clusters remains a significant challenge, necessitating real-time and accurately programmable robotic end-effector. To this end, we develop an innovative non-contact, precise particle cluster manipulation system with ultrasonic phased array transducer (PAT) under microscope. This system combines a physics-based deep learning algorithm for real-time calculation of phase-only holograms (POHs), supporting PAT to dynamically form acoustic fields, namely holographic acoustic end-effector (HAE). Leveraging the dynamically and accurately generated HAEs by our system, kinematics control of particle clusters including aggregation, rotation, and translation is yielded. The extensive experiments well demonstrated the effectiveness of proposed system for particle cluster manipulation.
Path planning processes in 3D environments with obstacles are essential for ensuring the successful navigation of Unmanned Aerial Vehicles (UAVs). Recently, the artificial intelligence theory presents increasingly eff...
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ISBN:
(纸本)9798350367607;9798350367591
Path planning processes in 3D environments with obstacles are essential for ensuring the successful navigation of Unmanned Aerial Vehicles (UAVs). Recently, the artificial intelligence theory presents increasingly effective algorithms and tools to address such a robotics challenge. This paper presents a comparative study of two most commonly used Reinforcement Learning (RL) algorithms, namely Q-learning and SARSA learning. Through numerical experimentations under different navigation scenarios with varying levels of complexity and increasing numbers of static obstacles, key performance metrics like path's length, total actions number, average reward, execution time and collision avoidance are considered and evaluated. The demonstrative results indicate that the Q-learning algorithm well addressed the challenges of UAVs' path planning in static environments. The performance of such an algorithm has proven to be satisfactory and more promising for UAVs' navigation in complex configuration spaces when compared to the SARSA algorithm.
In this study, we propose an efficient approach for recognizing harvesting information to perform grasping manipulation on fruits partially obscured by obstacles such as leaves and other fruits in an open-field orchar...
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Exploring the limits of quadruped robot agility, particularly in the context of rapid and real-time planning and execution of omnidirectional jump trajectories, presents significant challenges due to the complex dynam...
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ISBN:
(纸本)9798350377712;9798350377705
Exploring the limits of quadruped robot agility, particularly in the context of rapid and real-time planning and execution of omnidirectional jump trajectories, presents significant challenges due to the complex dynamics involved, especially when considering significant impulse contacts. This paper introduces a new framework to enable fast, omnidirectional jumping capabilities for quadruped robots. Utilizing minimum jerk technology, the proposed framework efficiently generates jump trajectories that exploit its analytical solutions, ensuring numerical stability and dynamic compatibility with minimal computational resources. The virtual model control is employed to formulate a Quadratic Programming (QP) optimization problem to accurately track the Center of Mass (CoM) trajectories during the jump phase. The whole-body control strategies facilitate precise and compliant landing motion. Moreover, the different jumping phase is triggered by time-schedule. The framework's efficacy is demonstrated through its implementation on an enhanced version of the open-source Mini Cheetah robot. Omnidirectional jumps-including forward, backward, and other directional-were successfully executed, showcasing the robot's capability to perform rapid and consecutive jumps with an average trajectory generation and tracking solution time of merely 50 microseconds.
Distance estimation from surrounding vehicles and roadside obstacles plays a crucial part and forms the core of various driver alerts in advanced driver assistance systems (ADAS) in life-threatening situations on the ...
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ISBN:
(纸本)9798350385939;9798350385922
Distance estimation from surrounding vehicles and roadside obstacles plays a crucial part and forms the core of various driver alerts in advanced driver assistance systems (ADAS) in life-threatening situations on the road. Unfortunately, given the high price point at which ADAS components are built, primarily due to the expensive radars and Lidars, the benefits of these systems remain exclusive to specific car segments. The present study attempts to democratize ADAS usage in the vehicle industry by adopting the vision-only approach, thereby making it affordable. The work focuses on building and evaluating algorithms for vehicle detection, classification, and distance estimation using a monocular camera mounted on a vehicle. Two methods have been developed and evaluated: (a) camera-optics-based and (b) image-based deep-learning depth estimation model. The evaluation metrics show promising results for the proposed image-based depth estimation with error correction model, which has the least RMSE and variation in the residuals.
A new mechanism of missile agile turn and its control method are proposed for problem of missile attacking rear targets in this paper. Firstly, a new agile turn mechanism for missiles is defined;Secondly, the dynamic ...
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This paper focuses on the development and optimization of a temperature control system utilizing a Proportional Integral-Derivative (PID) controller, with integration of MATLAB and Python. The work presented in this p...
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The fault diagnosis technology of spacecraft controlsystems is a crucial component of spacecraft health management. Traditional fault diagnosis technologies, such as model-based diagnosis and signal processing, are r...
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