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International Conference on Ubiquitous Robots (UR)

作者： Joon-Ha Kim Young-Ha Shin Hyobin Jeong Jun-Ho Oh Hae-Won Park Department of Mechanical Engineering Humanoid Research Center School of Mechanical Aerospace & Systems Engineering Korea Advanced Institute of Science and Technology Daejeon Republic of Korea Rainbow Robotics Company Daejeon Republic of Korea

This paper proposes a real-time footstep planning framework based on the A* footstep planning algorithm. The proposed footstep planner utilizes an energy consumption-based cost function to generate energy efficient navigation plan. To increase the computational efficiency, the cost-to-go heuristic function, which approximates the remaining cost to reach the goal, is modeled more precisely by considering the angle difference between the robot and the goal position. Furthermore, an efficient dual-level feasibility check is done to avoid occlusion with the environment while stepping over small objects if possible. Finally, the proposed footstep planning algorithm is integrated with the mapping algorithm and the walking controller to solve the humanoid navigation problem and validated in simulation and real-world experiments.

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Impedance Estimation of a Nonlinear Flexible mechanical Transmission using a Dual EKF

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IFAC-PapersOnLine 2022年第1期55卷 315-320页

作者： Sananda Chatterjee Soumen Sen Saikat Majumder School of Mechatronics and Robotics Indian Institute of Engineering Science and Technology Shibpur India Robotics & Automation Div. CSIR-CMERI: Central Mechanical Engineering Research Institute Govt. of India Durgapur 713209 India

In applications like human friendly robots, fast walking machines, exoskeletons and prosthetic devices, the recent trends select actuation system with physical joint flexibility. Series-elastic-actuation offers a method to achieve this flexibility having an actuator and an elastic transmission in series. In general, on having an inherent passive damping effect along with elasticity, the transmission will behave as a mechanical impedance element. In operating the transmission system, it is required to know the impedance components reliably. The best possible transmission model also is approximate only and may produce erroneous results with varying behaviour of the passive transmission with time environment condition. This paper proposes a Dual Extended Kalman Filter based method for on-line estimation of the transmission impedance of such a passive damped series-elastic transmission. The estimation is based on measurements of position and force. The effectiveness of the proposed estimator is shown through experiments on a transmission with an exponential spring and nonlinear damper, developed for a variable impedance actuator.

关键词： Nonlinear mechanical Transmission Affine Stiffness-Force Relation Dual EKF

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Safety-Critical Control Under Multiple State and Input Constraints and Application to Fixed-Wing UAV

Safety-Critical Control Under Multiple State and Input Const...

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IEEE Conference on Decision and Control

作者： Donggeon David Oh Dongjae Lee H. Jin Kim Department of Mechanical and Aerospace Engineering Seoul National University Seoul South Korea Department of Aerospace Engineering and the Automation and Systems Research Institute (ASRI) Seoul National University Seoul South Korea

This study presents a framework to guarantee safety for a class of second-order nonlinear systems under multiple state and input constraints. To facilitate real-world applications, a safety-critical controller must consider multiple constraints simultaneously, while being able to impose general forms of constraints designed for various tasks (e.g., obstacle avoidance). With this in mind, we first devise a zeroing control barrier function (ZCBF) using a newly proposed nominal evading maneuver. By designing the nominal evading maneuver to 1) be continuously differentiable, 2) satisfy input constraints, and 3) be capable of handling other state constraints, we deduce an ultimate invariant set, a subset of the safe set that can be rendered forward invariant with admissible control inputs. Thanks to the development of the ultimate invariant set, we then propose a safety-critical controller, which is a computationally tractable one-step model predictive controller (MPC) with guaranteed recursive feasibility. We validate the proposed framework in simulation, where a fixed-wing UAV tracks a circular trajectory while satisfying multiple safety constraints including collision avoidance, bounds on flight speed and flight path angle, and input constraints.

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Learning Goal-oriented Bimanual Dough Rolling Using Dynamic Heterogeneous Graph Based on Human Demonstration

arXiv

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arXiv 2024年

作者： Liu, Junjia Li, Chenzui Wang, Shixiong Dong, Zhipeng Calinon, Sylvain Li, Miao Chen, Fei The Department of Mechanical and Automation Engineering T-Stone Robotics Institute The Chinese University of Hong Kong Hong Kong The Idiap Research Institute Martigny Switzerland The School of Microelectronics The Institute of Technological Sciences Wuhan University Wuhan China

Soft object manipulation poses significant challenges for robots, requiring effective techniques for state representation and manipulation policy learning. State representation involves capturing the dynamic changes in the environment, while manipulation policy learning focuses on establishing the relationship between robot actions and state transformations to achieve specific goals. To address these challenges, this research paper introduces a novel approach: a dynamic heterogeneous graph-based model for learning goal-oriented soft object manipulation policies. The proposed model utilizes graphs as a unified representation for both states and policy learning. By leveraging the dynamic graph, we can extract crucial information regarding object dynamics and manipulation policies. Furthermore, the model facilitates the integration of demonstrations, enabling guided policy learning. To evaluate the efficacy of our approach, we designed a dough rolling task and conducted experiments using both a differentiable simulator and a real-world humanoid robot. Additionally, several ablation studies were performed to analyze the effect of our method, demonstrating its superiority in achieving human-like behavior. Copyright © 2024, The Authors. All rights reserved.

关键词： Anthropomorphic robots

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Robust Attitude Control of Multibody Aircraft with Preview-Based Control Compensation 6th

Robust Attitude Control of Multibody Aircraft with Preview...

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6th China Aeronautical Science and Technology Conference, CASTC 2023

作者： Qi, Pengyuan Li, Qingxian Mou, Quanrun Wang, Yinan Research Institute for Frontier Science Beihang University Beijing100191 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Large Aircraft Advanced Training Center Beihang University Beijing100191 China Department of Mechanical Materials and Aerospace University of Liverpool LiverpoolL69 3BX United Kingdom

ISBN: (纸本)9789819988662

This paper investigates the robust attitude control for wingtip-connected multibody aircraft, using preview-based control compensation mechanism to address the issues of inherent wingtip couplings. A constrained multibody dynamics model is first derived to obtain the nonlinear and linearised formulations for multibody aircraft. The H∞ control is employed to synthesize the pitch angle and forward velocity controller in the longitudinal channel, while the H∞ preview control is employed to synthesize the roll angle and yaw rate controller in the lateral channel. The preview control scheme enables the usage of future reference commands as feedforward information to synthesize appropriate control compensation to reduce the impact of wingtip couplings between adjacent aircraft units. Simulation studies conducted based on the nonlinear model show that the preview-based H∞ control system is able to achieve better control effectiveness and disturbance rejection performance, compared to the baseline regular H∞ control system without preview. These demonstrate that the mechanism of control compensation can greatly benefit the flight control of multibody aircraft. © 2024, Chinese Society of Aeronautics and Astronautics.

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Dynamic Characterization and Phenomenological Modelling of Customizable Pneumatic Artificial Muscle 7

Dynamic Characterization and Phenomenological Modelling of C...

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7th IEEE International Conference on Electronics, Computing and Communication Technologies, CONECCT 2021

作者： Arora, Aman Sarkar, Debadrata Sen, Soumen Kumar, Amit Roy, Shibendu Shekhar National Institue of Technology Durgapur Department of Mehcanical Engineering Durgapur India Robotics and Automation Group CSIR-Central Mechanical Engineering Research Institute Durgapur Durgapur India

ISBN: (纸本)9781665428491

Pneumatic Artificial Muscles (PAMs) are gaining popularity over traditional actuators in applications where the requirement are high force density, low mass, biological muscle like characteristics, etc,. Especially in applications related to Human Robot Interactions and wearable active devices, these actuators are considered much safe due to their light weight when compared to their commercial counterparts. However their usage are limited, due to their inherent nonlinearities, which poses challenges in their accurate force and position control. The article focuses on dynamic characterization of an in-house fabricated PAM using a three-element lumped phenomenological model. The model consists of a spring element, contractile force element and a damper element arranged in parallel. Pressure perturbation experiments have been conducted to identify the parameters in the governing equations for the spring coefficient, damping coefficient and the contractile element force. Finally, the developed model has been validated by reasonably predicting the displacement response of the PAM to a triangular pressure input pulse when subjected to a constant load on a dynamic test rig. © 2021 IEEE.

关键词： Human robot interaction

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A Modular End Effector with Active Rolling Fingertip for Picking Cloth-Like Objects 19

A Modular End Effector with Active Rolling Fingertip for Pic...

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19th IEEE International Conference on automation Science and engineering, CASE 2023

作者： Zhang, Kun Yang, Yuanhang Chen, Zhiming Chen, Hua Wang, Michael Yu Zhang, Wei Robotics Institute Hong Kong University of Science and Technology Clear Water Bay Hong Kong School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China Hkust Shenzhen-Hong Kong Collaborative Innovation Research Institute Futian Shenzhen China Monash University Department of Mechanical & Aerospace Engineering ClaytonVIC3800 Australia

ISBN: (纸本)9798350320695

Cloth-like items are ubiquitous in both daily life and industrial production, but their softness makes them difficult to manipulate. This paper focuses on solving the problem of automatic manipulation especially in the scenario of flat surface by introducing a novel end-effector mechanism. The gripper utilizes a modular design concept, enabling it to be reconstructed with a varying number of fingers based on specific requirements. One of the fingers has an active rolling fingertip that rolls up the object from the table to create wrinkles, for easier grasping. Additionally, there are fingertips with revolute joints that enable fine-tuning of the grasp configuration to fix the objects. To test the effectiveness of the mechanism, we manufactured a real gripper device and mounted it on a collaborative robotic arm for grasping tests. Experiments were conducted on six kinds of cloth-like objects with different materials, grasping them from above. The experimental results show that the gripper with this mechanism configuration performs well in this scenario. © 2023 IEEE.

关键词： Grippers

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Sparsity via Sparse Group k-max Regularization

arXiv

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arXiv 2024年

作者： Tao, Qinghua Xi, Xiangming Xu, Jun Suykens, Johan A.K. STA-DIUS ESAT KU Leuven Belgium Research Center for Intelligent Robotics Zhejiang Lab Zhejiang Hangzhou China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen518055 China

For the linear inverse problem with sparsity constraints, the l0 regularized problem is NP-hard, and existing approaches either utilize greedy algorithms to find almost-optimal solutions or to approximate the l0 regularization with its convex counterparts. In this paper, we propose a novel and concise regularization, namely the sparse group k-max regularization, which can not only simultaneously enhance the group-wise and in-group sparsity, but also casts no additional restraints on the magnitude of variables in each group, which is especially important for variables at different scales, so that it approximate the l0 norm more closely. We also establish an iterative soft thresholding algorithm with local optimality conditions and complexity analysis provided. Through numerical experiments on both synthetic and real-world datasets, we verify the effectiveness and flexibility of the proposed method. © 2024, CC BY-NC-SA.

关键词： Iterative methods

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Renderable Street View Map-Based Localization: Leveraging 3D Gaussian Splatting for Street-Level Positioning

Renderable Street View Map-Based Localization: Leveraging 3D...

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

作者： Howoong Jun Hyeonwoo Yu Songhwai Oh Artificial Intelligence (IPAI) Seoul National University and Automation and Systems Research Institute (ASRI) and Sequor Robotics Inc. Seoul Korea Republic of Department of Intelligent Robotics & Mechanical Engineering Sungkyunkwan University (SKKU) Suwon-si Korea Republic of Department of Electrical and Computer Engineering (ECE) & Interdisciplinary Program in Artificial Intelligence (IPAI) Seoul National University and Automation and Systems Research Institute (ASRI) and Sequor Robotics Inc. Seoul Korea Republic of

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

In this paper, we introduce a new method that first utilizes 3D Gaussian splatting in street-level localization problem. Robust localization with street-level real-world images such as street view is a major issue for autonomous vehicle, augmented reality (AR) navigation, and outdoor mobile robots. The objective is to determine the position and orientation of a query image that matches a street view database composed of RGB images. However, given the limited information available in the street view images, accurately determining the location solely based on this data presents a significant challenge. To address this challenge, we propose a novel method called renderable street view map-based localization (RSM-Loc). This approach enhances the localization process by augmenting 2D street view images into a renderable 3D map using 3D Gaussian splatting, to resolve street-level localization problems. Upon receiving a query RGB image without geometry information, the proposed method renders 2D images from a pre-made renderable map and compares image pose similarities between the rendered images and the query image. Through iterations of this process, the proposed method eventually estimates the pose of the given query image. The experimental results demonstrate that RSM-Loc outperforms the baselines with neural-field-based localization. Additionally, we conduct deep analysis on the proposed method to show that our method can serve as a new concept for the street-level localization problem.

关键词： Location awareness Visualization Matched filters Three-dimensional displays Image resolution Navigation Noise measurement Mobile robots Intelligent robots Image reconstruction

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Development of an Autonomous Fish-Inspired Robotic Platform for Aquaculture Inspection and Management

Development of an Autonomous Fish-Inspired Robotic Platform ...

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IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)

作者： Gianluca Manduca Luca Padovani Edoardo Carosio Giorgio Graziani Cesare Stefanini Donato Romano The BioRobotics Institute & Department of Excellence in Robotics and AI Scuola Superiore Sant’Anna Pisa Italy Department of Mechanical and Aerospace Engineering Sapienza University CNR-INM Marine Technology Research Institute Rome Italy Department of Mechanical and Aerospace Engineering Sapienza University Rome Italy

Aquaculture applications are increasingly utilizing precision techniques such as computer vision technologies to perform a variety of inspection tasks. This work presents the development of three activities essential for the creation of a biomimetic robotic platform with onboard intelligence and autonomous task execution capabilities. The proposed robot is inspired by carangiform movement and achieves various trajectories through a magnetic actuation system with a single motor for propulsion. Fluid dynamics studies can improve the performance of the proposed propulsion system, thus ensuring greater energy efficiency. Thanks to its modular and scalable structure, the platform can integrate different components such as a vision system. The investigated vision-based model shows promising results for deployment in marine environments and can be adapted to detect various marine species. This fish-inspired robot platform has potential applications in the sustainable inspection and management of aquaculture facilities.

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