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On Simplified models of Position Servo Actuators for control purposes

On Simplified Models of Position Servo Actuators for control...

引用

2021 international conference on Control, automation and Diagnosis, ICCAD 2021

作者： Kelly, Rafael Zepeda, Gabriela Monroy, Carmen DET-DFA CICESE Research Center B.C. Ensenada22860 Mexico ISEP Sistema Educativo Estatal Zona 01 Calle Ruiz No. 57 B.C. Ensenada22800 Mexico

ISBN: (纸本)9781665449687

This paper deals with modeling of position servo actuators built around Permanent Magnet Direct Current (PMDC) motors which are utilized in low cost robotics and *** specifically, two simplified models are proposed: first a static ideal model and then a dynamic realistic *** the proposed dynamic model, this paper attempts to capture the observed behavior of some position servoes in real life practice. In a first time it is shown that Proportional-Integral-Derivative (PID) control and Proportional (P) one are able to global regulate shaft positioning of PMDC motors under disturbances free situations. This is the main argument to justify the P dominant feedback control approach at the core of most position servo actuators. © 2021 IEEE.

关键词： robotics

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Multi-robot Informative Path Planning using a Leader-Follower Architecture

Multi-robot Informative Path Planning using a Leader-Followe...

引用

IEEE international conference on robotics and automation (ICRA)

作者： Di Caro, Gianni A. Yousaf, Abdul Wahab Ziaullah

ISBN: (纸本)9781728190778

We consider typical scenarios where an autonomous multi-robot team is used for surveying a large region. The desired output is a spatial map of the physical values of interest. Accounting for spatial correlation and uncertainty, the map is modeled using a Gaussian Process. Considering real-world constraints such as limited time budget and collision avoidance, we model team's mission as a joint informative path planning problem which is tackled using a leader-follower architecture balancing centralized and fully distributed computation of plans. The leader first identifies a convex containment region that is to be sampled by the team. Next, through a combination of Bayesian optimization and Monte Carlo simulation, distinct sampling locations are identified and assigned to the followers. Each follower independently solves an orienteering problem to find a collision-free path maximizing information gain. A team-level adaptive replanning criterion is designed to keep redirecting sampling towards the most informative regions. The algorithm has been validated in computational experiments for map estimation. Compared to a baseline reference algorithm, it has shown a significantly higher accuracy. Moreover, the approach has shown good ability to support network connectivity, as well as good scalability in computation.

关键词： Monte Carlo methods Uncertainty Computational modeling Scalability Robot kinematics Computer architecture Path planning

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Segmentation of Fish in the Natural Habitat Using Deep Learning for Fish Size Measurement Application 7

Segmentation of Fish in the Natural Habitat Using Deep Learn...

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7th international conference on Green Technology and Sustainable Development, GTSD 2024

作者： Nguyen, Quang-Huy Le, Hoang-Minh-Quang Tran, Thi-Thao Nguyen, Tuan Ninh Pham, Van-Truong School of Electrical and Electronic Engineering Hanoi University of Science and Technology Department of Automation Engineering Hanoi Viet Nam

ISBN: (纸本)9798350386073

Assessing the size of fish in their natural habitat could provide crucial information for managing and monitoring these resources, thereby enabling the development of sustainable fishing and resource conservation strategies. However, manual methods are time-consuming, labor-intensive, and can have adverse effects on the health of the fish. Therefore, this study proposes a novel automated monitoring method by utilizing fish image segmentation, which allows for easier estimation of their size. Our proposed model namely AquaAttSeg has Ushape architecture with an encoder and a decoder. AquaAttSeg utilizes the PVTv2-B3 model as the backbone of encoder to enhance the ability to extract semantic information from input. In contrast to conventional U-shape models that directly connect low-level features from the encoder to high-level features in the decoder, leading to information imbalance, we proposed the HFIM module, which includes two our proposed modules SAM and CAM to replace conventional skip connections in order to enhance important information from the encoder to the decoder and enhance the processing of low-level features to extract more semantic information before combine with high-level features to reduce the information imbalance. In the decoder stage, we also proposed the Convmix Transpose Custom block, which can effectively synthesize rich and multidimentional information between the encoder and decoder to efficiently recover lost information and enhance the performance of the model. The performance of our proposed model has been tested on two datasets including Deepfish dataset and SUIM dataset. Additionally, we have compared the results of our model with other state-of-the-art models, demonstrating that our model produces highly competitive and promising outcomes. © 2024 IEEE.

关键词： Fish

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Autonomous Vehicle Motion Planning via Recurrent Spline Optimization

Autonomous Vehicle Motion Planning via Recurrent Spline Opti...

引用

IEEE international conference on robotics and automation (ICRA)

作者： Xu, Wenda Wang, Qian Dolan, John M. Carnegie Mellon Univ ECE Pittsburgh PA 15213 USA Clemson Univ Int Ctr Automot Res CU ICAR Appl Dynam & Control Grp Greenville SC 29607 USA Carnegie Mellon Univ Fac Robot Inst Pittsburgh PA 15213 USA

ISBN: (纸本)9781728190778

Trajectory planning in dynamic environments can be decomposed into two sub-problems: 1) planning a path to avoid static obstacles, 2) then planning a speed profile to avoid dynamic obstacles. This is also called path-speed decomposition. In this work, we present a novel approach to solve the first sub-problem, motion planning with static obstacles. From an optimization perspective, motion planning for autonomous vehicles can be viewed as non-convex constrained nonlinear optimization, which requires a good enough initial guess to start and is often sensitive to algorithm parameters. We formulate motion planning as convex spline optimization. The convexity of the formulated problem makes it able to be solved fast and reliably, while guaranteeing a global optimum. We then reorganize the constrained spline optimization into a recurrent formulation, which further reduces the computational time to be linear in the optimization horizon size. The proposed method can be applied to both trajectory generation and motion planning problems. Its effectiveness is demonstrated in challenging scenarios such as tight lane changes and sharp turns.

关键词： Smoothing methods Three-dimensional displays Trajectory planning Dynamics Planning Splines (mathematics) Vehicle dynamics

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Autonomous Exploration of Unknown 3D Environments Using a Frontier-Based Collector Strategy

Autonomous Exploration of Unknown 3D Environments Using a Fr...

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IEEE international conference on robotics and automation (ICRA)

作者： Iván D. Changoluisa Caiza Ana Milas Marco A. Montes Grova Francisco Javier Pérez-Grau Tamara Petrovic University of Zagreb Faculty of Electrical Engineering and Computing LARICS Laboratory for Robotics and Intelligent Control Systems Zagreb Croatia Advanced Center for Aerospace Technologies (CATEC) Aerospace Technology Park of Andalusia Seville Spain

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Autonomous exploration using unmanned aerial vehicles (UAVs) is essential for various tasks such as building inspections, rescue operations, deliveries, and warehousing. However, there are two main limitations to previous approaches: they may not be able to provide a complete map of the environment and assume that the map built during exploration is accurate enough for safe navigation, which is usually not the case. To address these limitations, a novel exploration method is proposed that combines frontier-based exploration with a collector strategy that achieves global exploration and complete map creation. In each iteration, the collector strategy stores and validates frontiers detected during exploration and selects the next best frontier to navigate to. The collector strategy ensures global exploration by balancing the exploitation of a known map with the exploration of unknown areas. In addition, the online path replanning ensures safe navigation through the map created during motion. The performance of the proposed method is verified by exploring 3D simulation environments in comparison with the state-of-the-art methods. Finally, the proposed approach is validated in a real-world experiment.

关键词： Three-dimensional displays Video on demand Navigation Warehousing Buildings Inspection Web sites

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Active Bayesian Multi-class Mapping from Range and Semantic Segmentation Observations

Active Bayesian Multi-class Mapping from Range and Semantic ...

引用

IEEE international conference on robotics and automation (ICRA)

作者： Asgharivaskasi, Arash Atanasov, Nikolay Univ Calif San Diego Dept Elect & Comp Engn La Jolla CA 92093 USA

ISBN: (纸本)9781728190778

Many robot applications call for autonomous exploration and mapping of unknown and unstructured environments. Information-based exploration techniques, such as Cauchy-Schwarz quadratic mutual information (CSQMI) and fast Shannon mutual information (FSMI), have successfully achieved active binary occupancy mapping with range measurements. However, as we envision robots performing complex tasks specified with semantically meaningful objects, it is necessary to capture semantic categories in the measurements, map representation, and exploration objective. This work develops a Bayesian multi-class mapping algorithm utilizing rangecategory measurements. We derive a closed-form efficiently computable lower bound for the Shannon mutual information between the multi-class map and the measurements. The bound allows rapid evaluation of many potential robot trajectories for autonomous exploration and mapping. We compare our method against frontier-based and FSMI exploration and apply it in a 3-D photo-realistic simulation environment.

关键词： Solid modeling Uncertainty Semantics Probabilistic logic Bayes methods Trajectory Velocity measurement

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Shared Control of Robot-Robot Collaborative Lifting with Agent Postural and Force Ergonomic Optimization

Shared Control of Robot-Robot Collaborative Lifting with Age...

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IEEE international conference on robotics and automation (ICRA)

作者： Rapetti, Lorenzo Tirupachuri, Yeshasvi Ranavolo, Alberto Kawakami, Tomohiro Yoshiike, Takahide Pucci, Daniele Ist Italiano Tecnol Ctr Robot Technol Dynam Interact Control Genoa Italy Univ Manchester Machine Learning & Optimisat Manchester Lancs England INAIL Dept Occupat & Environm Med Epidemiol & Hyg Rome Italy Honda Res & Dev Co Ltd Saitama Japan

ISBN: (纸本)9781728190778

Humans show specialized strategies for efficient collaboration. Transferring similar strategies to humanoid robots can improve their capability to interact with other agents, leading the way to complex collaborative scenarios with multiple agents acting on a shared environment. In this paper we present a control framework for robot-robot collaborative lifting. The proposed shared controller takes into account the joint action of both the robots thanks to a centralized controller that communicates with them, and solves the whole-system optimization. Efficient collaboration is ensured by taking into account the ergonomic requirements of the robots through the optimization of posture and contact forces. The framework is validated in an experimental scenario with two iCub humanoid robots performing different payload lifting sequences.

关键词： Smoothing methods Ergonomics Force Collaboration Humanoid robots Grasping Torque measurement

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Teach and Repeat Navigation: A Robust Control Approach

Teach and Repeat Navigation: A Robust Control Approach

引用

IEEE international conference on robotics and automation (ICRA)

作者： Payam Nourizadeh Michael Milford Tobias Fischer QUT Centre for Robotics Queensland University of Technology Brisbane Australia

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Robot navigation requires an autonomy pipeline that is robust to environmental changes and effective in varying conditions. Teach and Repeat (T&R) navigation has shown high performance in autonomous repeated tasks under challenging circumstances, but research within T&R has predominantly focused on motion planning as opposed to motion control. In this paper, we propose a novel T&R system based on a robust motion control technique for a skid-steering mobile robot using sliding-mode control that effectively handles uncertainties that are particularly pronounced in the T&R task, where sensor noises, parametric uncertainties, and wheel-terrain interaction are common challenges. We first theoretically demonstrate that the proposed T&R system is globally stable and robust while considering the uncertainties of the closed-loop system. When deployed on a Clearpath Jackal robot, we then show the global stability of the proposed system in both indoor and outdoor environments covering different terrains, outperforming previous state-of-the-art methods in terms of mean average trajectory error and stability in these challenging environments. This paper makes an important step towards long-term autonomous T&R navigation with ensured safety guarantees.

关键词： Uncertainty Navigation Wheels Robot sensing systems Robustness Odometry Mobile robots

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Research on energy saving of hydraulic system of hydraulic brick press 2

Research on energy saving of hydraulic system of hydraulic b...

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2nd international conference on Artificial Intelligence, automation, and High-Performance Computing, AIAHPC 2022

作者： Zheng, HongBo Li, MingJun Wang, ZhouLin Yang, JunHao College of Robotics Guangdong Polytechnic of Science and Technology Guangdong Zhuhai519090 China

ISBN: (纸本)9781510657717

In view of the problem of high energy consumption of ordinary hydraulic brick presses, the scheme of energy-saving transformation is proposed to replace the asynchronous motor with AC permanent magnet synchronous servo motor. The simulation models of the ordinary hydraulic brick press and the reformed servo direct drive pump-controlled hydraulic brick press are established in AMESim, and the energy consumption simulation and analysis are carried out. The results show that the modified servo direct drive pump-controlled hydraulic brick press is 20.7% more energy-saving than before the transformation. The reasons for energy saving lies in that, compared with the ordinary hydraulic brick press, the servo direct drive pump-controlled hydraulic brick press saves overflow loss in the pressure holding stage and reduces the dormant loss in the dormant stage. © 2022 SPIE. All rights reserved.

关键词： Brick

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Lyapunov-Based Kinematic Anti-Prance Control for a Modular Rimless-Wheel Exploration Rover

Lyapunov-Based Kinematic Anti-Prance Control for a Modular R...

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international conference on Control, automation, robotics and Vision (ICARCV)

作者： Walter Schindler German Aerospace Center (DLR) Institute of System Dynamics and Control Weßling Germany

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

The Scout rover is a novel rover concept developed by the German Aerospace Center (DLR) for the exploration of extreme extraterrestrial environments. Its locomotion platform is designed to tackle rough and rugged terrain, rock and boulder traverses, craters and cave systems on foreign celestial bodies. The Scout features a modular design with a compliant rover backbone and elastic rimless wheels. The backbone consists of rigid segments which are coupled by elastic vertebrae in-between. Under unfavorable conditions, the backbone deflects vertically, individual segments rear up and the rover begins to prance. Unintended backbone deformation and rearing-up negatively affect rover locomotion capabilities. This contribution presents a robust kinematic chassis controller for monitoring and controlling the backbone configuration. The backbone deformation is generically modeled upon an elementary backbone unit based on the nonlinear beam theory and a kinematic surrogate model. Lyapunov theory is used to synthesize a backbone controller upon the surrogate model for the elementary backbone unit. A kinematic chassis controller is established upon the elementary backbone controller in order to reduce unintended backbone deformations on chassis level. The overall controller is verified by means of test scenarios on different terrains on the Scout outdoor testbed. The controller significantly reduces backbone deformation on rough terrains.

关键词： Deformable models automation Deformation Wheels Kinematics Rocks Robots Monitoring

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