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Keypoints Estimation on Partial Point Clouds

Keypoints Estimation on Partial Point Clouds

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International Conference on robotics and Artificial Intelligence (ICRAI)

作者： Maryam Saleem Mohammad Zohaib Syed Abbas Zilqurnain Naqvi Department of Mechatronics & Control Engineering Human Centered Robotics Lab UET Lahore Pakistan SIGMA Clermont University of Clermont Auvergne Aubiere France

ISBN: (数字)9798350355703

ISBN: (纸本)9798350355710

Estimating 3D keypoints of an object has achieved considerable interest, especially in computer graphics and ma-chine vision. The complexity of the problem increases when the object is noisy, decimated, or partially occluded. To this end, we present an approach to estimate 3D keypoints from the partial PCDs such that they also highlight the object's missing parts. It is based on two modules: shape completion and keypoints estimation. The first module computes the object's missing parts and generates a dense shape which is used by the second module to estimate semantically and geometrically consistent keypoints. The approach also estimates confidence scores that allow the selection of valid keypoint considering the object's structure. We evaluate the proposed method for four different backbones and observe that we get better results using PointNet. Furthermore, the presented results show that the Percentage of Correct Keypoints (PCK) and Dual Alignment Score (DAS) for the keypoints estimated from the dense shapes (36.61 and 76.29) are 23.51 % and 12.14% higher, respectively, compared to those estimated from the partial objects (13.10 and 64.15).

关键词： Point cloud compression Industries Three-dimensional displays Accuracy Shape Estimation Computer graphics Complexity theory Noise measurement robotics and automation

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Kinematic Modeling of Serial Robotic Manipulators to Automate the Packaging Process of Tuna Cans

Kinematic Modeling of Serial Robotic Manipulators to Automat...

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IEEE Latin American robotics Symposium, LARS

作者： Clevex Rodriguez Ventura Maikol Sánchez Bacilio Leonardo Guimaraes Zavaleta Jose Cornejo Ricardo Palomares Professional School of Mechatronics Engineering Universidad Nacional de Trujillo Trujillo Peru Universidad Tecnologica el Peru Lima Peru Research Group of Advanced Robotics and Mechatronics (GI-ROMA) Universidad Ricardo Palma

ISBN: (数字)9798331508807

ISBN: (纸本)9798331508814

During 2024, the food and fishing derivatives industry contributed to the growth of Peru’s gross domestic product (GDP) by 5.28%. Only during the years 2020-2021, the “food and beverage products industry” presents a production of canned frozen fish and seafood of $\mathbf{9 4 8 4 2}$ MT. This publication presents the kinematic modeling and trajectory planning of two serial manipulators to automate the tuna can packaging process. A robotic system is proposed where tuna cans are placed and sorted inside boxes by a 3-DOF SCARA robot and these are packaged by a 6-DOF anthropomorphic robot. The calculation of the forward kinematics was carried out using the DenavitHartenberg convention and the inverse kinematics using the geometric method and kinematic decoupling for both serial manipulators. A trajectory planner was developed in Matlab R2021a that uses a 4-3-4 polynomial interpolator to generate position, velocity and acceleration profiles with smooth and coordinated movements. CoppeliaSim Edu 4.5.1 and SolidWorks 2021 software were used to integrate kinematic modeling, trajectory generation and present the simulation of the tuna can packaging environment. As future work, dynamic modeling and dynamic control of both robots will be developed to simulate the automated tuna can packaging process in CoppeliaSim.

关键词： Trajectory planning Economic indicators Robot kinematics 3-DOF Kinematics Packaging 6-DOF Trajectory MATLAB Robots

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Motion control of an internally-actuated cubical robot balancing on its edge 2

Motion control of an internally-actuated cubical robot balan...

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2nd IEEE International Conference on Control, Measurement and Instrumentation, CMI 2021

作者： Patil, Saurabh Chatterjee, Sananda Bhaumik, Subhasis Indian Institute of Engineering Science and Technology School of Mechatronics and Robotics Shibpur Howrah West Bengal India

ISBN: (纸本)9781728193427

The Internally-Actuated robots have recently gained popularity due to their ability of achieving controlled mobility (via moving or spinning internal inertial elements) even in milli/ micro gravity environment. In this paper such an internally actuated robot, cubical in shape, is considered and the dynamical equation of the robot is obtained. Aiming to achieve features like controlled tumbling and balancing on the edges, which are necessary for such robots to effectively execute their popular applications such as exploration of smaller solar-system bodies and self assembly of group robots, a stabilizing controller is proposed. The performance and robustness results of the proposed controller are also presented. The comparison results obtained, indicate the superiority of the proposed controller over the ones available in the literature. © 2021 IEEE.

关键词： Controllers

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Improved Contact Stability for Admittance Control of Industrial Robots with Inverse Model Compensation

Improved Contact Stability for Admittance Control of Industr...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Kangwagye Samuel Kevin Haninger Sami Haddadin Sehoon Oh Chair of Robotics and Systems Intelligence Munich Institute of Robotics and Machine Intelligence (MIRMI) Technical University Munich Munich Germany Department of Mechanical and Production Engineering Kyambogo University Kampala Uganda Department of Automation Fraunhofer IPK Berlin Germany Department of Robotics and Mechatronics Engineering DGIST Daegu Korea

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Industrial robots have increased payload, repeatability, and reach compared to collaborative robots, however, they have a fixed position controller and low intrinsic admittance. This makes realizing safe contact challenging due to large contact force overshoots in contact transitions and contact instability when the environment and robot dynamics are coupled. To improve safe contact on industrial robots, we propose an admittance controller with inverse model compensation, designed and implemented outside the position controller. By including both the inner loop and outer loop dynamics in its design, the proposed method achieves expanded admittance in terms of increasing both gain and cutoff frequency of the desired admittance. Results from theoretical analyses and experiments on a commercial industrial robot show that the proposed method improves rendering of the desired admittance while maintaining contact stability. We further validate this by conducting actual assembly tasks of plug insertion with fine positioning, switch insertion onto the rail, and colliding the robot end effector with random objects and surfaces, as seen at https://***/8XfkdHEdWDs.

关键词： Service robots Contacts Dynamics Cutoff frequency Observers Industrial robots Stability analysis Admittance Thermal stability Payloads

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Dynamics Analysis of a Symmetric 3-R(SRS)RP Multi-loop Mechanism 1

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23rd IFToMM China International Conference on Mechanism and Machine Science and engineering, IFToMM CCMMS 2022

作者： Li, Chuanyang Qin, Zhongbao Hu, Changhua Liu, Rongqiang Liu, Ruiwei Song, Xiaoke PLA Rocket Force University of Engineering Xi’an710025 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150080 China College of Naval Architecture and Ocean Engineering Guangzhou Maritime University GuangZhou510725 China School of Mechatronics and Vehicle Engineering East China Jiaotong University Nanchang330013 China

ISBN: (数字)9789811993985

ISBN: (纸本)9789811993978

The 3-R(SRS)RP multi-loop Mechanism is regarded as one module of a multi-stage manipulator for space manipulation operations, such as capturing free-flying objects. The mechanism has two rotational and one translational degrees of freedom, as well as includes coupled kinematic chains, which can be constructed to the modular system for space operation. The dynamics analysis of the mechanism is the basis of its structural design and actuation control. In this paper, the twist shaping matrix between the twists of links and the input rate array is derived by decoupling the mechanism and motion analysis. Based on the Newton–Euler equation, the dynamics model of the mechanism is established. the theoretical values of actuation power consumption on the certain motion modes is calculated via programming, then being compared with the simulation values obtained through ADAMS model. The results are basically consistent, which verifies the correctness of the dynamics analysis of the mechanical system. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Dynamics

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Deep Reinforcement Learning Based Mobile Robot Navigation in Unknown Environment with Continuous Action Space 5

Deep Reinforcement Learning Based Mobile Robot Navigation in...

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5th International Conference on Intelligent Autonomous Systems, ICoIAS 2022

作者： Phueakthong, Phuwanat Varagul, Jittima Pinrath, Nattawat School of Mechatronics Engineering Suranaree University of Technology Nakhon Ratchasima Thailand School of Manufacturing Automation and Robotics Engineering Suranaree University of Technology Nakhon Ratchasima Thailand School of Industrial Engineering Suranaree University of Technology Nakhon Ratchasima Thailand

ISBN: (数字)9781665498388

ISBN: (纸本)9781665498388

This work aims to propose the use of deep reinforcement learning for mobile robot navigation and obstacle avoidance in previously unknown areas or without pre-made maps with continuous action control to increase the capabilities of mobile robots beyond conventional map-based navigation. Deep reinforcement learning is used to enable the robot to learn how to make decisions and interact with the environment observed from sensor data to safely navigate itself to its destination. The robot has a two-dimensional laser scanner, ultrasonic sensors and odometry sensor. Deep Deterministic Policy Gradient, which can function in continuous action space, was chosen as the deep reinforcement learning model. The robot is trained and tested in a Gazebo simulator with Robot Operating System. After the training process, the robot is put to the challenge to complete a waypoint navigation mission in four unknown areas as part of an assessment. The results indicate that the mobile robot is adaptable and has the capability of traveling to the specified waypoints and completing the job without the need for a pre-drawn route or an obstacle map in unidentified environments with the minimum success rate of 69.7 percent. © 2022 IEEE.

关键词： Reinforcement learning

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Action-Driven Tactile Object Exploration for Shape Reconstruction via Silver Nanowire Injected Sensors

Action-Driven Tactile Object Exploration for Shape Reconstru...

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IEEE/SICE International Symposium on System Integration

作者： Tleukhan Mussin Yermakhan Kassym Nurlan Kabdyshev Marat Kaikanov Zhanat Kappassov School Engineering and Digital Sciences Nazarbayev University Dept. of Robotics and Mechatronics Nazarbayev University Astana Kazakhstan Physics Department Nazarbayev University

We present an action-driven tactile exploration system using flexible touch sensors integrated into the fingertips of a robot hand. These sensors are made from foams injected with silver nanotubes that exhibit resistance changes under pressure to enable tactile perception. A microcontroller-based unit captures the resistance, with communication deployed using the Robot Operating System. Our approach is evaluated in tactile object exploration, where robotic finger movements estimate the coordinates of the points of contact upon collisions with an object. Through repeated grasps, a point cloud of the shape of an object is generated. Distinct finger movements, or affordances, are developed to collect new contact points to discriminate four different shapes, including cube, cylinder, pyramid, and sphere. We benchmark our approach on medium and large sets of objects.

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Approximate Neural Network-based Nonlinear Model Predictive Control of Soft Continuum Robots

Approximate Neural Network-based Nonlinear Model Predictive ...

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IEEE/ASME International Conference on Mechtronic and Embedded Systems and Applications, MESA

作者： Hend Abdelaziz Abdullah Ahmed Haitham El-Hussieny Department of Mechatronics and Robotics Engineering Egypt-Japan University of Science and Technology (E-JUST) New Burg El-Arab City Alexandria Egypt

ISBN: (数字)9798331516239

ISBN: (纸本)9798331516246

This paper employs a deep learning approach to enhance the task space control of soft continuum robots. We built an approximate data-driven dynamics model of a soft robot using sampled Cartesian positions of the robot’s tip and its actuator tensions. We then incorporated this surrogate model into a Model Predictive Control (MPC) control scheme, enabling nonlinear control for task space trajectory tracking without relying on an exact analytical dynamics model of the robot or extensive computations. By involving constraints into the MPC, we addressed the robot’s workspace and actuation limits. The numerical results of the simulation experiment show that deep learning dynamic models can improve robotic control. This leads to accurate trajectory tracking and suggests that deep learning could be used more in robot system control, especially for real-time control applications.

关键词： Deep learning Trajectory tracking Computational modeling Predictive models Aerospace electronics Soft robotics Control systems Numerical models Continuum robots Predictive control

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Investigations on the Design and Simulation of Smart Irrigation Robot for Nurseries

Investigations on the Design and Simulation of Smart Irrigat...

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Advances in Computing, Communication, Embedded and Secure Systems (ACCESS), International Conference on

作者： B. Abhiram Swati Jha Y. Yogendra Sai Prasad Joshuva Arockia Dhanraj V. Ramkumar Department of Mechatronics Engineering Centre for Automation & Robotics Hindustan Institute of Technology and Science Chennai Tamil Nadu India

The irrigation systems in nurseries can be the cause of various water supply errors- ranging from lack of sufficient water supply to over-watering and imbalance in the water pH levels. Based on the statistics recorded by the department of agriculture and farmers welfare, we have conducted we concluded that the water supply management and plant life maintenance are the major problems. Considering all these real-time errors, we have designed a smart irrigation robot functioning on the inputs from a group of soil moisture sensors which helps eliminate the monotonous task of monitoring and keeping records of the change in soil moisture.

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Towards Instance Segmentation-Based Litter Collection with Multi-Rotor Aerial Vehicle

Towards Instance Segmentation-Based Litter Collection with M...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Filip Zoric Antonio Franchi Matko Orsag Zdenko Kovacic Chiara Gabellieri Laboratory for Robotics and Intelligent Control Systems (LARICS) at the Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia Robotics and Mechatronics Group from the University of Twente Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy

ISBN: (数字)9798350357882

ISBN: (纸本)9798350357899

This paper presents a novel aerial robotics application of instance segmentation-based floating litter collection with a multi-rotor aerial vehicle (MRAV). In the scope of the paper, we present a review of the available datasets for litter detection and segmentation. The reviewed datasets are used to train a Mask-RCNN neural network for instance segmentation. The neural network is off-board deployed on an edge computing device and used for litter position estimation. Based on the estimated litter position, we plan a path based on a quadratic Bezier curve for the litter pickup. We compare different trajectory generation methods for the object pickup. The system is verified in a laboratory environment. Eventually, we present practical considerations and improvements necessary to enable autonomous litter collection with MRAV.

关键词： Instance segmentation Reviews Neural networks Laboratories Estimation Trajectory Aircraft

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