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Cam Profile Optimization for a Piezoelectric-Based Sole Energy Harvester

Cam Profile Optimization for a Piezoelectric-Based Sole Ener...

引用

IEEE International Conference on robotics and Biomimetics

作者： Haisu Liao Zhongliang Ren Yidi Wang Xinyu Wu Fei Gao Southern University of Science and Technology Shenzhen China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Harvesting energy from the human body to extend the operational time for low-power has gained significant attention. Recently, researchers have focused on biomechanical energy harvesting from human feet while walking. This paper presents an optimization of the cam profile for a piezoelectric-based sole energy harvester designed to be worn on the bottom of shoes to power electronic devices. Specifically, cams with linear polynomial and exponential functions were designed to actuate the piezoelectric transducers (PZTs). Force analysis revealed that the exponential function cam induces more significant deformation in the PZTs than the linear polynomial cam. Preliminary tests on a healthy subject validated this design, showing that the exponential function cam produced an average output power of 0.16mW at a walking speed of 5.5 km/h, indicating a 78% improvement over the linear polynomial cam. Moreover, the optimization rate increased with the growing walking speed.

关键词： Legged locomotion Deformation Force Voltage Polynomials Energy harvesting Power generation Optimization Lead zirconate titanate Testing

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SmallRhex: A Fast and Highly-Mobile Hexapod Robot

SmallRhex: A Fast and Highly-Mobile Hexapod Robot

引用

IEEE International Conference on robotics and Biomimetics

作者： Wenhui Wang Wujie Shi Zerui Li Weiheng Zhuang Zheng Zhu Zhenzhong Jia Department of Mechanical and Energy Engineering Southern University of Science and Technology (SUSTech) Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Uni-versities Shenzhen China

ISBN: (纸本)9781665481106

Relying on the unique C-leg structure, RHex robots have good mobility and traffic ability when having relatively simple structures. Based on the existing RHex robots, taking into account the performance and cost, this design develops a small hexapod robot, named smallRhex, with low cost but strong performance. This paper mainly introduces the mechanical structure, robot gaits, simulation, and physical performance tests of smallRhex robots. The hardware is mainly based on the raspberry pie microcomputer and Robomaster motor and accessories. The high power density meets the dual requirements of performance and cost. Then cooperates with 3D printing and sheet metal and machined parts processing to complete the design of the mechanical structure and assembly of the robot. At the control level, raspberry pie directly controls the movement of 6 motors. The gait design includes basic motion gait, which includes straight walking and turning, and other gaits of complex motion: stair climbing, jumping, and high obstacle climbing. They are simulated in Webots. Finally, the performance test and the gait test of the robot are carried out. Then the gait design is further optimized, and the basic design of smallRhex robot is completed.

关键词： Legged locomotion Power system measurements Costs Metals Stairs Microcomputers Turning

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Design and preliminary testing of a piezoelectric-based sole energy harvester

Design and preliminary testing of a piezoelectric-based sole...

引用

2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Wang, Yidi Zhao, Xuan Shi, Qiuyu Liao, Haisu Wu, Xinyu Gao, Fei Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen518055 China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen518055 China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Shatin999077 Hong Kong

ISBN: (纸本)9781665481090

Harvesting energy from the human body to replenish existing energy sources is receiving substantial attention. Recently scientists have been focusing on harvesting biomechanical energy from human feet during walking. This paper develops a piezoelectric-based sole energy harvester that is designed to be worn on the bottom of shoes to harvest energy, thus powering wearable electronic devices. Specifically, a cam with piezoelectric(PZT) stacks is mounted on the heel to scavenge energy during the heel strike. The cam can change the input's direction from the vertical direction to the horizontal direction. In addition, the output power of this part can be optimized or improved by generating a specified cam profile. A bimorph piezoelectric plate is installed on the forefoot to convert the toes' bending deformation into electricity. Herein, piezoelectric Macro Fiber Composites (MFC) are employed to capture the large deformation. Preliminary testing on a healthy subject is conducted to validate this design. The average power output of the harvester is 8.83 m W. © 2022 IEEE.

关键词： Cams

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Semantic Mapping Based on Visual SLAM with Object Model Replacement Visualization for Cleaning Robot

Semantic Mapping Based on Visual SLAM with Object Model Repl...

引用

IEEE International Conference on robotics and Biomimetics

作者： Zirui Wang Haiou Liao Zhenzhong Jia Jing Wu Department of Mechanical and Energy Engineering Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems they are also with Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology (SUSTech) Shenzhen China

ISBN: (纸本)9781665481106

Cleaning robots have been widely used in our daily life, achieving huge success in the service robot sector. The autonomous movement and decision-making of these robots directly depend on their environmental perception capability, which is implemented using SLAM (simultaneous localization and mapping) technique. In order to achieve better environmental perception and intelligent decision-making, it is necessary to introduce visual SLAM into cleaning robot and take full advantage of visual information to achieve higher-level perception, instead of sticking to current feature point or pixel level perception capability. In this paper, we propose a framework for semantic mapping with object model replacement visualization in indoor scenes for cleaning robot. We use an EKF-based method to fuse wheel odometry and visual odometry, and build a map representation for navigation in the framework. We obtain a semantic map by fusing object detection and point cloud segmentation. We also develop object model replacement for better visualization purposes. Finally, we conduct dataset tests and real experiments to validate our proposed framework.

关键词： Visualization Simultaneous localization and mapping Service robots Biological system modeling Semantics Decision making Wheels

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Magnetically Driven Capsule Robot for Multi-Targeted Biopsy and Drug Delivery in Stomach

Magnetically Driven Capsule Robot for Multi-Targeted Biopsy ...

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IEEE International Conference on robotics and Biomimetics

作者： Zhihui Xu Tanyong Wei Zongze Li Ding Huang Shoubin Liu Chengzhi Hu Department of Mechanical and Energy Engineering Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Southern University of Science and Technology Shenzhen China Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China

Capsule robots have emerged as a promising solution for non-invasive and painless screening of gastrointestinal diseases, offering significant advantages in patient comfort and reduced risk of cross-infection. Despite these advantages, existing capsule robots fall short in their ability to conduct targeted biopsies and deliver drugs to specific gastric lesions. To address this limitation, this paper presents the design and development of a magnetically driven capsule robot that leverages visual feedback to achieve accurate targeting for biopsy and drug administration in gastric lesions. Internal magnets, responsive to an external gradient magnetic field, enable the controlled propulsion of the capsule robot. A kinetic model of the capsule robot is analyzed, allowing it to recognize lesion contours through the endoscopic camera. This recognition determines the rotation angle or small adjustments required for the capsule robot's attitude and positioning. Experimental results in a simplified in vitro stomach model showcase the capability of the capsule robot to achieve targeted biopsy and drug delivery. These results highlight the potential feasibility of the proposed capsule robot in enhancing diagnostic accuracy and treatment efficacy with broader applications within the realm of gastric healthcare.

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Design of Capsule Robot for Magnetic Gastric Biopsy and Drug Administration

Design of Capsule Robot for Magnetic Gastric Biopsy and Drug...

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IEEE International Conference on Mechatronics and Automation

作者： Zhihui Xu Zongze Li Shoubin Liu Chengzhi Hu Department of Mechanical and Energy Engineering Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Southern University of Science and Technology Shenzhen China Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen China School of Mechanical and Electrical Engineering Harbin Institute of Technology Shenzhen China

Capsule robots have emerged as a promising tool for the early diagnosis of gastrointestinal diseases. Unlike conventional gastroscopy, they offer the potential for minimally invasive or even non-invasive treatment, and can alleviate discomfort and pain in patients. However, current capsule robots have some limitations. For instance, they lack stomach tissue biopsy and drug administration functions, and the capsule robot used for biopsy does not consider the tolerance of gastrointestinal tissue. Similarly, the capsule robot used for drug administration does not account for the outlet speed of drug administration. This paper proposes a new biopsy method using a magnetically manipulated capsule robot and analyzes the principles governing the robot's manipulation during the biopsy and drug administration processes. Furthermore, an ANSYS gastric model was established and used to simulate and experimentally analyze damage to the gastric tissue model from different types of biopsy needles and their moving speeds. The appropriate type of biopsy needle and moving speed were determined to prevent damage to the gastric tissue. The study also used FLUENT to determine the appropriate thrust at the entrance of the drug cavity and the impact of the drug density on the drug outlet velocity to ensure complete adherence of the drug to the lesion.

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Robust Dynamic Object Removal in 3D Point Clouds Based on Multi-View Projections

Robust Dynamic Object Removal in 3D Point Clouds Based on Mu...

引用

International Conference on Advanced robotics and Mechatronics (ICARM)

作者： Chen Yao Jingyi Liu Xing Yao Dingyuan Zhang Zheng Zhu Zhenzhong Jia Department of Mechanical and Energy Engineering Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Southern University of Science and Technology (SUSTech) Shenzhen China Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities SUSTech Shenzhen China Shenzhen Zhicheng Software Technology Service corporation Futian Shenzhen Guangdong China Shenzhen ETop Information corporation Futian Shenzhen Guangdong China

ISBN: (数字)9798350385724

ISBN: (纸本)9798350385731

SLAM techniques are always used to effectively explore surroundings. To further enhance navigation capabilities, it is essential to filter out dynamic and noisy objects. In this paper, we present an online method that employs a multi-view image-parameterization-based representation, specifically a Bird’s Eye View-Polar View-Range View (BEV-PV-RV) fusion module, for efficient removal of dynamic objects in 3D point clouds. By employing different sizes of projected image windows and varying resolution levels, we can generate confidence levels that determine the disparity between the query scans and the imprecise noisy map derived from a collection of point clouds. Importantly, these points are identified at a granular level. Our iterative process combines the strengths of different projected views, compensating for motion distortions and comparison errors. To evaluate the effectiveness of our approach, we conducted extensive experiments on different sequences of the KITTI dataset. This allows us to successfully eliminate dynamic points, recover static points, and construct a subset that consists mainly of static points with the aid of proposed projected image views. Both quantitative and qualitative analyses demonstrate the robustness, reliability, and high performance of such proposed method.

关键词： Point cloud compression Laser radar Three-dimensional displays Simultaneous localization and mapping Navigation Statistical analysis Heuristic algorithms Robustness Sensors Noise measurement

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6DoF-ICTC: A Deep Image Feature Extraction Network Combining Transformers and CNNs for 6DoF Pose Estimation 12

6DoF-ICTC: A Deep Image Feature Extraction Network Combining...

引用

12th International Conference on CYBER Technology in Automation, Control, and intelligent systems, CYBER 2022

作者： Zhang, Liming Zhou, Xin Zhu, Baixian Wang, Can Wu, Xinyu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Cas Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology China University of Science and Technology of China China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

In this work, we propose a new image feature extraction network for 6D pose estimation tasks. The majority of existing 6D pose estimation networks are based on the RGBD input, which is the fusion of images and point clouds. They are mainly working on keypoint extraction, point cloud feature extraction, and other tasks, however, image features, on the other hand, mainly rely on CNN networks that are currently advanced. With the development of Vision Transformer in the field of computer vision, the results on ImageNet demonstrate its benefit of extracting global features, and we see new directions that the Transformers can bring to the area of image feature extraction. ICTC is a Transformer paired with a CNN network that fuses the retrieved global features into each pixel and then does local feature extraction. This provides greater robustness to 6D pose estimation In complex situations such as shifting lighting conditions and object occlusion. Our method achieves 96% accuracy using the average ADD metric on the LineMOD dataset, demonstrating our method's effectiveness. © 2022 IEEE.

关键词： Feature extraction

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SWhegPro: A Novel Robust Wheel-Leg Transformable Robot

SWhegPro: A Novel Robust Wheel-Leg Transformable Robot

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IEEE International Conference on robotics and Biomimetics

作者： Cunxi Dai Xiaohan Liu Jianxiang Zhou Zhengtao Liu Zheng Zhu Zhenzhong Jia Department of Mechanical and Energy Engineering The Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Southern University of Science and Technology (SUSTech) Shenzhen China Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities SUSTech Shenzhen China

ISBN: (纸本)9781665481106

This paper reports the design, implementation, and performance evaluation of SWhegPro, a swift and robust wheel-leg transformable robot that can operate under heavy payload. SWhegPro can shift wheel morphology between the wheel, e-shape leg, and S-shape leg, the corresponding gaits were developed and compared in simulation. The wheel/leg operation is driven by the same motor, so the actuation system and power can be utilized efficiently. Different from its predecessor which uses tendon-driven transformation mechanisms, SWhegPro utilizes self-locking electric push rods as transformation actuators. This makes it possible for SWhegPro to operate under heavy loads and is easier to repair. The robot was empirically built, and the design process, mechatronics infrastructure, and gait behavioral development were discussed. The performance of the robot was evaluated in various sce-narios, including driving and turning in wheeled mode, step crossing, and irregular terrain passing in legged mode.

关键词： Legged locomotion Performance evaluation Mechatronics Biomimetics Wheels Morphology Maintenance engineering

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Different Height Stairs Climbing Pattern Generation for Humanoids

Different Height Stairs Climbing Pattern Generation for Huma...

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IEEE International Conference on Real-time Computing and robotics (RCAR)

作者： Ming Yang Dingkui Tian Minjia Xu Feng Li Jianquan Sun Weiwei Shang Xinyu Wu University of Science and Technology of China Hefei P. R. China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Daqing Vocational College Daqing China SIAT-CUHK Joint Laboratory of Robotics and Intelligent Systems Shenzhen China

Climbing stairs has been an indispensable ability for humanoids. This paper presents a novel and practical problem: climbing stairs of varying heights. In this study, the humanoid is modeled as an inverted pendulum and set the pelvis trajectory on the vertical axis, representing the center of mass (CoM), as a quadratic function. We also use a polynomial to design the ZMP and CoM trajectory on the horizontal plane. To generate the CoM trajectory, the sliding mode controller is utilized to track the reference trajectory. To eliminate chattering of the sliding mode controller, the universal approximation property of the radial basis function (RBF) network is leveraged to approximate the switching law. Finally, simulation experiments are performed in CoppeliaSim, and the biped robot is capable of walking stably and quickly.

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