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2024 IEEE International Conference on Unmanned Systems, ICUS 2024

作者： Zhang, Shaojie Ni, Fenglei Li, Xueai Li, Xu Ji, Yi Shao, Xiangyu State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China Key Laboratory of Autonomous Intelligent Unmanned Systems Harbin Institute of Technology Harbin China

ISBN: (纸本)9798350384185

Robustness walking and recovery ability in uneven terrains and unexpected collisions are crucial for the practical application of humanoid ***, existing methods struggle to effectively balance stability, motion safety and walking *** paper proposes a hybrid control strategy combing Nonlinear Model Predictive Control (NMPC) and Whole-Body Control (WBC) to improve the robot's walking stability and reaction safety in collisions *** NMPC generates long-term and macroscopic movements, with capture point theory being utilized for foot placements determination under external *** this foundation, the WBC regulates the robot refinedly in real-time based on task priorities and *** verify the effectiveness of the proposed method, involving uneven terrain walking and external impacts rejection. © 2024 IEEE.

关键词： Anthropomorphic robots

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Versatile Jumping of Humanoid Robots via Curriculum-Assisted Reinforcement Learning

Versatile Jumping of Humanoid Robots via Curriculum-Assisted...

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2024 China Automation Congress, CAC 2024

作者： Tan, Ruiyu Li, Xueai Ni, Fenglei Zhou, Dong Ji, Yi Shao, Xiangyu Key Laboratory of Autonomous Intelligent Unmanned Systems Harbin Institute of Technology Harbin China State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China

ISBN: (纸本)9798350368604

Versatile jumping is crucial for agile and adaptive behavior of humanoid robots in complex environments. However, humanoid robots have to manage impact forces while maintaining balance and stability throughout the take-off, flight, and landing phases, which imposes significant challenges for motion planning and controller design. This paper proposes a curriculum-assisted reinforcement learning framework for the humanoid robot to achieve various jumping tasks. The curriculum learning divides the jump training process into multi-stages and design different episodes in each stage to guarantee the training feasibility and generalize learned skills. Simulations on a 28 DOFs humanoid robot verify the excellent diverse jumping capability of the proposed policy. This exploration of different tasks also proves the policy’s robustness, allowing the robot quickly recover from perturbations using a variety of learned maneuvers. © 2024 IEEE.

关键词： Anthropomorphic robots

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A Novel Low-Cost, Recyclable, Easy-to-Build Robot Blimp For Transporting Supplies in Hard-to-Reach Locations 13

A Novel Low-Cost, Recyclable, Easy-to-Build Robot Blimp For ...

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13th Annual IEEE Global Humanitarian Technology Conference, GHTC 2023

作者： Li, Karen Hou, Shuhang Negash, Matyas Xu, Jiawei Jeffs, Edward D'Antonio, Diego S. Saldana, David Lehigh University BethlehemPA United States Lehigh University Autonomous and Intelligent Robotics Laboratory -AirLab PA United States

ISBN: (纸本)9798350321326

Rural communities in remote areas often encounter significant challenges when it comes to accessing emergency healthcare services and essential supplies due to a lack of adequate transportation infrastructure. The situation is further exacerbated by poorly maintained, damaged, or flooded roads, making it arduous for rural residents to obtain the necessary aid in critical situations. Limited budgets and technological constraints pose additional obstacles, hindering the prompt response of local rescue teams during emergencies. The transportation of crucial resources, such as medical supplies and food, plays a vital role in saving lives in these situations. In light of these obstacles, our objective is to improve accessibility and alleviate the suffering of vulnerable populations by automating transportation tasks using low-cost robotic systems. We propose a low-cost, easy-to-build blimp robot (UAVs), that can significantly enhance the efficiency and effectiveness of local emergency responses. © 2023 IEEE.

关键词： Budget control

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A practical PID variable stiffness control and its enhancement for compliant force-tracking interactions with unknown environments

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Science China(Technological Sciences) 2023年第10期66卷 2882-2896页

作者： ZHANG Xin ZHOU Hao LIU JinGuo JU ZhaoJie LENG YuQuan YANG ChenGuang State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China University of Chinese Academy of Sciences Beijing 100049China School of Computing University of PortsmouthPortsmouth PO13HEUK Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy EngineeringSouthern University of Science and TechnologyShenzhen 518055China Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and EngineeringSouth China University of TechnologyGuangzhou 510640China

Compliant interaction control is a key technology for robots performing contact-rich manipulation *** design of the compliant controller needs to consider the robot hardware because complex control algorithms may not be compatible with the hardware performance,especially for some industrial robots with low bandwidth *** paper focuses on effective and easy-to-use compliant control algorithms for position/velocity-controlled *** by human arm stiffness adaptation behavior,a novel variable target stiffness(NVTS)admittance control strategy is proposed for adaptive force tracking,in which a proportional integral derivative(PID)variable stiffness law is designed to update the stiffness coefficient of the admittance function by the force and position ***,its stability and force-tracking capability are theoretically *** addition,an impact compensator(Impc)is integrated into the NVTS controller to enhance its disturbance-suppression capability when the robot is subjected to strong vibration disturbances in complicated surface polishing *** proposed controllers are validated through four groups of experimental tests using different robots and the corresponding results demonstrate that they have high-accuracy tracking capability and strong adaptability in unknown environments.

关键词： compliant interaction control force tracking PID variable stiffness impact compensator unknown environments

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Machine Learning-based Optimal Trajectory Planning for Spacecraft Passively Flying Around a Satellite for Proximity Operations

Machine Learning-based Optimal Trajectory Planning for Space...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Barth, Andrew Roach, Dylan Ma, Ou Hernandez, Michael Ashbaugh, Ryan Fleming, Alex Department of Aerospace Engineering Intelligent Robotics and Autonomous Systems Laboratory University of Cincinnati CincinnatiOH45221 United States iMETALX Inc SausalitoCA94965 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

In-space or On-orbit Servicing, Assembly, and Manufacturing (ISAM or OSAM) activities require spacecraft to fly around a client satellite or another orbiting object in a proximity range from 100’s of meters to 0 meters in distance. When performing such proximity operations, it becomes extremely important for the servicing craft to not only avoid collision but at the same time fly close enough for better situational awareness and minimal fuel consumption. This is especially important because such orbiting spacecraft will often be low-cost CubeSats performing OSAM tasks, therefore, planning a Passive Relative Orbit (PRO) becomes essential for low-risk and energy-efficient operations. Next, the problem of how to deploy a CubeSat from a station-keeping Chief spacecraft along a transfer trajectory, followed by a PRO-based two-impulse burn maneuver with minimal fuel consumption and variable time constraints, needs to be solved. Once the task is completed, another two-burn transfer trajectory will be calculated for the servicing deputy to return to the Chief. In this paper, we use a machine learning approach to determine the ΔV burns required to achieve the relative transfer and task trajectories. Machine learning allows us to improve our mission planning capabilities and gives the system more freedom to make choices where the operator does not have clear or full insight of the complex physics under many constraints. The system was trained using the proximal policy optimization algorithm for a range of task trajectory parameters randomly selected for each training episode. The results of the trained system were validated by comparison to those produced by traditional optimization methods from our previous work. The robustness of the trained algorithm was verified by 1,000 random scenarios falling within the range of trained conditions. The study demonstrates the ability to use the trained model for a variety of situations without the need to retrain specially for each type

关键词： Orbits

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Saliency-SLAM: Saliency Prediction for Visual SLAM

Saliency-SLAM: Saliency Prediction for Visual SLAM

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2023 Tianjin University-IET Electrical and Information Engineering Doctoral Forum, TJU IET 2023

作者： Jin, Sheng Meng, Qinghao Institute of Robotics and Autonomous Systems Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System School of Electrical and Information Engineering Tianjin University Tianjin China

ISBN: (纸本)9781839539824

This paper proposes a novel approach for visual simultaneous localization and mapping (vSLAM), called Saliency-SLAM. This method effectively emulates the visual attention mechanism by integrating a saliency prediction model. In contrast to conventional vSLAM methods, which treat all feature points as equally significant, salient feature points are given greater importance in Saliency-SLAM. Therefore, we construct a novel saliency dataset specifically for vSLAM task to train a saliency prediction model by integrating multi-level visual information. Then, we propose to use the salient value of predicted result as the weight of significance for the feature points during the optimization process. Exhaustive experiments have been conducted on the KITTI dataset, demonstrating that our proposed method outperforms existing approaches in terms of localization accuracy. © The Institution of Engineering & Technology 2023.

关键词： Forecasting

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The Spinning Blimp: Design and Control of a Novel Minimalist Aerial Vehicle Leveraging Rotational Dynamics and Locomotion

arXiv

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arXiv 2025年

作者： Santens, Leonardo D’Antonio, Diego S. Hou, Shuhang Saldaña, David Autonomous and Intelligent Robotics Laboratory –AIRLab Lehigh University BethlehemPA18015 United States

This paper presents the Spinning Blimp, a novel lighter-than-air (LTA) aerial vehicle designed for low-energy stable flight. Utilizing an oblate spheroid helium balloon for buoyancy, the vehicle achieves minimal energy consumption while maintaining prolonged airborne states. The unique and low-cost design employs a passively arranged wing coupled with a propeller to induce a spinning behavior, providing inherent pendulum-like stabilization. We propose a control strategy that takes advantage of the continuous revolving nature of the spinning blimp to control translational motion. The cost-effectiveness of the vehicle makes it highly suitable for a variety of applications, such as patrolling, localization, air and turbulence monitoring, and domestic surveillance. Experimental evaluations affirm the design’s efficacy and underscore its potential as a versatile and economically viable solution for aerial applications. © 2025, CC BY-NC-SA.

关键词： Airships

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Active Camera View Planning Based on Deep Reinforcement Learning in Indoor Exploration 42

Active Camera View Planning Based on Deep Reinforcement Lear...

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42nd Chinese Control Conference, CCC 2023

作者： Wang, Hao-Yu Meng, Qing-Hao Dai, Xu-Yang Institute of Robotics and Autonomous Systems School of Electrical and Information Engineering Tianjin University Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System Tianjin300072 China

ISBN: (纸本)9789887581543

In the last decades, significant progress has been made in the field of active vSLAM (visual simultaneous localization and mapping). However, the majority of active vSLAM methods suffer from the problem of coupling the camera's viewpoint to the robot's motion, which limits the initiative during the exploration of unknown environments. To address this issue, this study proposes a camera view planning method based on deep reinforcement learning (DRL), which makes the camera rotate independently. First, feature encoding is performed on the reconstructed navigation map using a multi-layer convolutional neural network (CNN). Second, the DRL-based camera view planning method is trained through the proximal policy optimization (PPO) algorithm. Last, a significant number of tests is performed on a public dataset of indoor environments. The simulation results show that the proposed camera view planning method improves the exploration coverage by an average of 4% (33.86 m2 for traditional vs. 35.21 m2 for the suggested method). Meanwhile, the kind of semantic information newly observed in each step increases by 21% (2.9 for traditional vs. 3.5 for the proposed method) on average, indicating the improvement in the efficiency of information acquisition. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Reinforcement learning

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Finding Optimal Modular Robots for Aerial Tasks

Finding Optimal Modular Robots for Aerial Tasks

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IEEE International Conference on robotics and Automation (ICRA)

作者： Jiawei Xu David Saldaña Autonomous and Intelligent Robotics Laboratory (AIRLab) Lehigh University PA USA

Traditional aerial vehicles have limitations in their capabilities due to actuator constraints, such as motor saturation. The hardware components and their arrangement are designed to satisfy specific requirements and are difficult to modify during operation. To address this problem, we introduce a versatile modular multi-rotor vehicle that can change its capabilities by reconfiguration. Our modular robot consists of homogeneous cuboid modules, propelled by quadrotors with tilted rotors. Depending on the number of modules and their configuration, the robot can expand its actuation capabilities. In this paper, we build a mathematical model for the actuation capability of a modular multi-rotor vehicle and develop methods to determine if a vehicle is capable of satisfying a task requirement. Based on this result, we find the optimal configurations for a given task. Our approach is validated in realistic $\mathbf{3D}$ simulations, showing that our modular system can adapt to tasks with varying requirements.

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SBlimp: Design, Model, and Translational Motion Control for a Swing-Blimp

SBlimp: Design, Model, and Translational Motion Control for ...

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

作者： Jiawei Xu Diego S. D'Antonio Dominic J. Ammirato David Saldaña Autonomous and Intelligent Robotics Laboratory (AIRLab) Lehigh University PA USA

We present an aerial vehicle composed of a custom quadrotor with tilted rotors and a helium balloon, called SBlimp. We propose a novel control strategy that takes advantage of the natural stable attitude of the blimp to control translational motion. Different from cascade controllers in the literature that controls attitude to achieve desired translational motion, our approach directly controls the linear velocity regardless of the heading orientation of the vehicle. As a result, the vehicle swings during the translational motion. We provide a planar analysis of the dynamic model, demonstrating stability for our controller. Our design is evaluated in numerical simulations with different physical factors and validated with experiments using a real-world prototype, showing that the SBlimp is able to achieve stable translation regardless of its orientation.

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