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检索条件"任意字段=2024 International Conference on Intelligent Robotics and Automatic Control"

共 5236 条记录，以下是41-50 订阅

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Model-Based Position control of Energy-Efficient Electro-Hydraulic Linear Drives

Model-Based Position Control of Energy-Efficient Electro-Hyd...

引用

2024 international conference on intelligent robotics and automatic control

作者： Zhang, Xieli Padovani, Damiano Guangdong Technion Israel Inst Technol Dept Mech Engn Robot Shantou Guangdong Peoples R China

ISBN: (纸本)9798350389814;9798350389807

The rising interest in energy efficiency for hydraulic systems directs the research towards electro-hydraulic drives, namely linear actuators (i.e., hydraulic cylinders) directly coupled to pumps driven by electric motors. This approach removes functional power dissipations, enables energy recovery, and facilitates system commissioning. However, these drives are characterized by inherently low damping that causes unwanted payload oscillations and deteriorates the position control's accuracy of the actuator. Adding active damping via proper control techniques is essential. Hence, this paper develops a model-based design for closed-loop position control with the addition of high-pass-filtered pressure feedback. The model supports identifying crucial control parameters, such as the proportional and integral gains of the position feedback and the gain and time constant of the pressure feedback. This method is experimentally tested on a heavy-duty robotic manipulator. The results show that the payload oscillations are reduced dramatically, and the position tracking is accurate and robust for different load cases.

关键词： Feedback control position tracking fluidic actuators robotic manipulators

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Design of tourism interpretation system based on intelligent light control 6

Design of tourism interpretation system based on intelligent...

引用

6th international conference on robotics, intelligent control and Artificial Intelligence, RICAI 2024

作者： Shi, Luojing Marzuki, Azizan Wang, Hongrun Zhang, Qi School of Housing Building and Planning Universiti Sains Malaysia Penang Malaysia School of Electronic Engineering and Automation Guilin University of Electronic and Technology Guilin China

ISBN: (纸本)9798331541699

The emergence of smart tourism, propelled by the advancement of new-generation information technologies such as 5G, cloud computing, big data, and artificial intelligence (AI), has instigated transformative shifts in the tourism industry. This evolution has disrupted conventional marketing paradigms and heralded a new era for tourism. Smart optical technology has injected fresh momentum into the progression of tourism and facilitated significant advancements in smart tourism. This study explores a tourism interpretation system based on visible light communication (VLC). By harnessing variations in LED light sources, this system achieves automatic interpretation functions to offer users services including text, audio guidance, and intelligent navigation. These features enrich immersive experiences and cater to tourists’ individual needs. The intelligent light control tour guide system enhances the intelligence and interactivity of the tour, effectively showcasing the characteristics and value of tourism resources, while also fulfilling its educational function of interpretation. © 2024 IEEE.

关键词： Leisure

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Design of a Standard Wheelchair Extension Using a Semi-automatic Crawler System for Stair Mobilization with PID control for Motor Speed 7

Design of a Standard Wheelchair Extension Using a Semi-autom...

引用

7th international conference on Mechatronics, robotics and Automation

作者： Rivas Cerron, Jose Rodrigo Lopez Torres, Cristian Luis Matos Parado, Fernando Jesus Zarate Pena, Frank William Univ Continental EAP Mechatron Engn Huancayo Peru

ISBN: (纸本)9798350352481;9798350352474

In Peru, 2.76% of the population, equivalent to some 932,000 people, have motor disabilities and use wheelchairs. These people face accessibility problems due to the lack of inclusion in architecture, especially when using stairs. The research proposes to design a portable extension for wheelchairs, which allows users to go up and down stairs autonomously and safely, by means of a PID speed control. Although there are solutions such as ramps, lightweight chairs and motorized devices, most of them do not provide full autonomy to the user

关键词： Traction control unit climbing system autonomy linear actuator motor disability accessibility inclination sensor motor speed control automatic inclination system

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Water Surface Autonomus Navigation Simulation via Multi-agent Proximal Policy Optimization

Water Surface Autonomus Navigation Simulation via Multi-agen...

引用

2024 international conference on intelligent robotics and automatic control

作者： Yuan, Ziang Li, Yinghui Duan, Junwei City Univ Macau Fac Data Sci Macau Peoples R China Jinan Univ Sch Intelligent Syst Sci & Engn Guangzhou Peoples R China

ISBN: (纸本)9798350389814;9798350389807

To address the challenges of autonomous navigation and intelligent obstacle avoidance for clusters of homogeneous unmanned surface vehicles (USVs) in intricate environments, a self-driving algorithm utilizing multi-agent reinforcement learning (MARL) is introduced. A multi-obstacle scenario is created, where the interactions among unmanned underwater vehicles are used to assess the game situation. The USV fleet undergoes training through the multi-agent proximal policy optimization algorithm (MAPPO) to facilitate autonomous driving. This approach allows for efficient route planning and effective obstacle evasion, ensuring that the vehicles reach their destination with the desired orientation and relative positioning. The simulation environment is constructed with the Unity game engine, providing visualization during training to enhance algorithm robustness. Experimental results demonstrate that both the proposed algorithm and simulation setup exhibit strong feasibility and good performance.

关键词： Machine learning Reinforcement learning Multi-agent USV Obstacle avoidance

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A Bayesian Optimization Framework for the automatic Tuning of MPC-based Shared controllers

A Bayesian Optimization Framework for the Automatic Tuning o...

引用

IEEE international conference on robotics and Automation (ICRA)

作者： van der Horst, Anne Meere, Bas Krishnamoorthy, Dinesh Bakker, Saray van de Vrande, Bram Stoutjesdijk, Henry Alonso, Marco Torta, Elena Eindhoven Univ Technol Eindhoven Netherlands Delft Univ Technol Delft Netherlands Philips IGT Syst Mechatron Noord Brabant Netherlands

ISBN: (纸本)9798350384581;9798350384574

This paper presents a Bayesian optimization framework for the automatic tuning of shared controllers which are defined as a Model Predictive control (MPC) problem. The proposed framework includes the design of performance metrics as well as the representation of user inputs for simulation-based optimization. The framework is applied to the optimization of a shared controller for an Image Guided Therapy robot. VR-based user experiments confirm the increase in performance of the automatically tuned MPC shared controller with respect to a hand-tuned baseline version as well as its generalization ability.

关键词： Model predictive control

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Research on Robot Power Distribution Cabinet Operation Based on Machine Vision

Research on Robot Power Distribution Cabinet Operation Based...

引用

2024 international conference on intelligent robotics and automatic control

作者： Han, Shaofeng Li, Zhichao Teng, Wei North China Elect Power Univ Sch Energy Power & Mech Engn Beijing Peoples R China

ISBN: (纸本)9798350389814;9798350389807

In recent years, the field of machine vision has developed rapidly, enabling the extraction of increasingly detailed information from images. At the same time, robotics technology has also advanced swiftly, with robots being widely applied in daily life. In our research, we combined machine vision technology with robotics to study operations for power distribution cabinets. Our system is based on a six-degree-of-freedom robotic arm, with the robot's end effector using a two-finger parallel electric gripper and an RGB-D camera for visual data acquisition. We also proposed a vision processing method to identify the status of the power distribution cabinet and to recognize and calculate the rotation angle of knobs. The system, utilizing these methods, was integrated into a power distribution cabinet platform for experimental testing. The robot was then controlled to perform the corresponding tasks, achieving success rates of 100%, 80%, and 70% respectively. Therefore, our proposed vision processing method effectively identifies and calculates the position and angle of buttons and knobs, and the integrated system successfully completed the corresponding tasks.

关键词： machine vision robotics machine learning angle recognition

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Data-Driven Linear Quadratic Regulator using LightGBM for Quadcopter control

Data-Driven Linear Quadratic Regulator using LightGBM for Qu...

引用

IEEE international conference on automatic control and intelligent Systems (I2CACIS)

作者： Al Ghifari, Ahmad Musthafa Mahayana, Dimitri Harsoyo, Agung Inst Teknol Bandung Sch Elect Engn & Informat Bandung Indonesia

ISBN: (纸本)9798350372113;9798350372106

A quadcopter is an unmanned aerial vehicle that requires a control system to stabilize it during flight. In this paper, a data-driven control algorithm, Light Gradient Boost Machine (LightGBM) is proposed to improve the quadcopter control system. The input and output data we use for the LightGBM algorithm are obtained from a closed-loop quadcopter system with a linear quadratic regulator (LQR) controller. With the expectation that the LightGBM control algorithm can replace the LQR controller on the quadcopter. Simulations have been carried out in this study, and the results of the simulations show that the proposed algorithm has similar response results as LQR control, so that the proposed algorithm can be used as a control system in the quadcopter system.

关键词： Quadcopter control system machine learning Linear Quadratic Regulator (LQR) LightGBM

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Development of an automatic Sweet Pepper Harvesting Robot and Experimental Evaluation

Development of an Automatic Sweet Pepper Harvesting Robot an...

引用

IEEE international conference on robotics and Automation (ICRA)

作者： Pan, Qinghui Wang, Dong Lian, Jie Dong, Yongxiang Qiu, Chaochao Dalian Univ Technol Key Lab Intelligent Control & Optimizat Ind Equip Minist Educ Dalian 116024 Peoples R China Dalian Univ Technol Sch Control Sci & Engn Dalian 116024 Peoples R China

ISBN: (纸本)9798350384581;9798350384574

The aging population and diminishing working population in agriculture motivate the development of autonomous harvesting robots. Although autonomous harvesting is expanding rapidly, the commercial application of sweet pepper harvesting robots still faces challenges. This paper presents the development of a sweet pepper harvesting robot and reports its experimental verification, which mainly includes end-effector design, visual perception, and grasping pose control. The end-effector adopts electrical control, mainly composed of a servo-electric two-finger parallel clamping module, a swing-cutting module, and a fruit recovery device. Equipped with a tactile sensor array, it can accurately sense the sweet pepper peduncle position and the end-effector state (harvesting failure) to complete the precise cutting. An end-effector grasping pose control algorithm of the manipulator is proposed, which can control the end-effector to grasp along the direction of the fruit peduncle and perpendicular to the tangent direction of the picking point by estimating the pose of the sweet pepper peduncle. Finally, the robot and proposed method were verified in a plant factory. The experimental findings demonstrate that the developed harvesting robot can complete robust detection of fruit peduncles and non-destructive picking of sweet pepper, with an average picking time of about 15 seconds.

关键词： End effectors

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A Path Planning Method for Electric Vehicle Based on Q-Learning

A Path Planning Method for Electric Vehicle Based on Q-Learn...

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2024 international conference on intelligent robotics and automatic control

作者： Deng, Rong Huang, Ju Nantong Vocat Coll Sci & Technol Sch Informat & Intelligent Engn Nantong Peoples R China

ISBN: (纸本)9798350389814;9798350389807

The increasing adoption of electric vehicles (EVs) has intensified the demand for efficient navigation methods to locate charging stations, optimizing both user convenience and energy utilization. This paper proposes a Q-learning-based path planning approach that dynamically identifies optimal routes for EVs while considering real-world constraints such as traffic and charging station availability. The proposed model integrates grid-based environmental modeling with reinforcement learning to achieve robust and adaptive path optimization. Experimental results, conducted on simulated urban environments derived from real-world data, demonstrate the algorithm's ability to effectively navigate diverse scenarios, minimizing travel distance and avoiding obstacles. The findings highlight the potential of this approach to enhance EV navigation systems and lay a foundation for future research in high-complexity transportation networks.

关键词： Electric Vehicle (EV) Navigation Path Planning Q-learning Grid-Based Modeling

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Reinforcement Learning Strategies for Severely Unbalanced Drone

Reinforcement Learning Strategies for Severely Unbalanced Dr...

引用

IEEE international conference on automatic control and intelligent Systems (I2CACIS)

作者： Zaludin, Zairil Univ Putra Malaysia Dept Aerosp Engn Serdang Malaysia

ISBN: (数字)9798350372106

ISBN: (纸本)9798350372113;9798350372106

Quadcopter drones rely entirely on their four rotors to control altitude and attitude. A complete failure of any single rotor results in losing stability and control unless the controller can reconfigure the drone's remaining actuators to re-establish balance in forces and moments. Previous attempts to reinstate full stability and control for this type of unbalanced drone by using classical and modern control laws have been unsuccessful. Recent development in Artificial Intelligence technology, however, may suggest a new control solution to rescue the crippled drone. The work reported in this paper proposes the initial strategies to implement Reinforcement Learning technique to find an optimal solution by regulating the remaining rotor speeds. The mode chosen for the study is hovering. The strategy to train the Reinforcement Learning agent is also included.

关键词： fault-tolerant control quadcopter Reinforcement Learning agent unbalanced drone non-linear control

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