Pub Date : 2023-12-04DOI: 10.1109/ROBIO58561.2023.10354936
Liangjie Tu, Fugang Yi, Bingfei Fan, Mingyu Du, Shibo Cai
Elderly people are easy to suffer from accidental injuries due to loss-of-balance in daily life. Wearable sensing technology is promising for detecting or predicting loss-of-balance events. This paper proposes a human loss-of-balance prediction method based on a customized wearable plantar pressure sensing system. To realize accurate prediction of loss-of-balance, we integrate the simulated annealing algorithm (SA) and the random forest algorithm (RF) to construct a SA-RF prediction model, where the input of the model is the plantar pressure data of the feet and the output of the model is the label of the human motion state. To validate the effectiveness of the proposed SA-RF model, 15 healthy subjects participated in the experiments. The experimental results show that the classification and recognition accuracy of the SA-RF model are significantly improved compared to the RF model, especially for the recognition of the easily loss-of-balance state. The accuracy of the proposed SA-RF model reaches 90%, which is a 5% improvement compared to the RF model. Therefore, the use of the SA-RF model based on plantar pressure can effectively predict loss-of-balance and thus has the potential to be integrated into fall prevention applications.
{"title":"Prediction of Loss-of-Balance of the Human Based on Plantar Pressure by Using the SA-RF Algorithm","authors":"Liangjie Tu, Fugang Yi, Bingfei Fan, Mingyu Du, Shibo Cai","doi":"10.1109/ROBIO58561.2023.10354936","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354936","url":null,"abstract":"Elderly people are easy to suffer from accidental injuries due to loss-of-balance in daily life. Wearable sensing technology is promising for detecting or predicting loss-of-balance events. This paper proposes a human loss-of-balance prediction method based on a customized wearable plantar pressure sensing system. To realize accurate prediction of loss-of-balance, we integrate the simulated annealing algorithm (SA) and the random forest algorithm (RF) to construct a SA-RF prediction model, where the input of the model is the plantar pressure data of the feet and the output of the model is the label of the human motion state. To validate the effectiveness of the proposed SA-RF model, 15 healthy subjects participated in the experiments. The experimental results show that the classification and recognition accuracy of the SA-RF model are significantly improved compared to the RF model, especially for the recognition of the easily loss-of-balance state. The accuracy of the proposed SA-RF model reaches 90%, which is a 5% improvement compared to the RF model. Therefore, the use of the SA-RF model based on plantar pressure can effectively predict loss-of-balance and thus has the potential to be integrated into fall prevention applications.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"64 6","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139187001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-04DOI: 10.1109/ROBIO58561.2023.10354940
Junqiu Wang, Jianmei Tan, Peng Lin, Chenguang Xing, Bo Liu
We propose an effective stall recovery learning approach based on a soft actor-critic algorithm with smooth reward functions. Stalling is extremely dangerous for aircraft and unmanned aerial vehicles (UAVs) because altitude decreases can result in fatal accidents. Stall recovery policies perform appropriate control sequences to save aircrafts from such lethal situations. Learning stall recovery policies using reinforcement learning methods is desirable because such policies can be learned automatically. However, stall recovery training is challenging since the interplay between an aircraft and its environment is very complicated. In this work, the proposed stall recovery learning approach yields better performance than other methods. We successfully apply smooth reward functions to the learning process because reward functions are critical for the convergence of policy learning. We achieve good performance by applying reward scaling to the soft actor-critic algorithm with automatic entropy learning. Experimental results demonstrate that stalls can be successfully recovered using the learned policies. The comparison results show that our method provides better results than previous algorithms.
{"title":"Learning Stall Recovery Policies using a Soft Actor-Critic Algorithm with Smooth Reward Functions","authors":"Junqiu Wang, Jianmei Tan, Peng Lin, Chenguang Xing, Bo Liu","doi":"10.1109/ROBIO58561.2023.10354940","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354940","url":null,"abstract":"We propose an effective stall recovery learning approach based on a soft actor-critic algorithm with smooth reward functions. Stalling is extremely dangerous for aircraft and unmanned aerial vehicles (UAVs) because altitude decreases can result in fatal accidents. Stall recovery policies perform appropriate control sequences to save aircrafts from such lethal situations. Learning stall recovery policies using reinforcement learning methods is desirable because such policies can be learned automatically. However, stall recovery training is challenging since the interplay between an aircraft and its environment is very complicated. In this work, the proposed stall recovery learning approach yields better performance than other methods. We successfully apply smooth reward functions to the learning process because reward functions are critical for the convergence of policy learning. We achieve good performance by applying reward scaling to the soft actor-critic algorithm with automatic entropy learning. Experimental results demonstrate that stalls can be successfully recovered using the learned policies. The comparison results show that our method provides better results than previous algorithms.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"64 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139187005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-04DOI: 10.1109/ROBIO58561.2023.10354957
Yi Liu, Junyue Tang, Yafang Liu, Gongbo Ma, Feng Sun, Ye Li, Shengyuan Jiang
To exactly detect the water ice of the South Pole of the moon, a lunar regolith in-situ analysis payload deploying a mass spectrometer is proposed for China future lunar exploration missions. In order to receive the lunar regolith sample from a robotic arm with a soil sampler and transfer it into a furnace for further analysis, a sample manipulation mechanism is required during the above work flow. To solve the problems of adapting the sampler’s docking accuracy, receiving and transferring two different types of lunar soil sample under times of in-situ analysis, etc., a sample repetitive manipulation mechanism (SRMM) is proposed in this paper. By using a floating adjustable docking components and a flexible hopper, two types of encapsulated regolith sample and bulk material sample can be received with minimal sample loss, respectively. In order to receive and transfer two types of samples multiple times, two sample receiving methods have been designed that can be repeatedly transferred. A worm and worm wheel combined with a ball screw is designed in SRMM. To verify the above mechanism design, validation experiments were conducted. It indicates that this novel SRMM can be deployed in the future mission after further environmental tests.
{"title":"A Sample Repetitive Manipulation Mechanism (SRMM) for Lunar Regolith In-Situ Analysis: Design and Validation","authors":"Yi Liu, Junyue Tang, Yafang Liu, Gongbo Ma, Feng Sun, Ye Li, Shengyuan Jiang","doi":"10.1109/ROBIO58561.2023.10354957","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354957","url":null,"abstract":"To exactly detect the water ice of the South Pole of the moon, a lunar regolith in-situ analysis payload deploying a mass spectrometer is proposed for China future lunar exploration missions. In order to receive the lunar regolith sample from a robotic arm with a soil sampler and transfer it into a furnace for further analysis, a sample manipulation mechanism is required during the above work flow. To solve the problems of adapting the sampler’s docking accuracy, receiving and transferring two different types of lunar soil sample under times of in-situ analysis, etc., a sample repetitive manipulation mechanism (SRMM) is proposed in this paper. By using a floating adjustable docking components and a flexible hopper, two types of encapsulated regolith sample and bulk material sample can be received with minimal sample loss, respectively. In order to receive and transfer two types of samples multiple times, two sample receiving methods have been designed that can be repeatedly transferred. A worm and worm wheel combined with a ball screw is designed in SRMM. To verify the above mechanism design, validation experiments were conducted. It indicates that this novel SRMM can be deployed in the future mission after further environmental tests.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"41 5","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139187206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-04DOI: 10.1109/ROBIO58561.2023.10354986
Kohei Nishikawa, Y. Origane, Daisuke Kurabayashi
Modular robots are expected to be used in extreme environments owing to their adaptability, and various modular robots have been developed. Most studies have focused on the expandability of capabilities or the integration of modules, whereas only a few studies have investigated autonomous decentralized control, in which each module harmonizes its own movements for overall functionality. We developed an underwater modular robot that synchronizes its paddle strokes; the robot is based on the motif of Gonium, a multicellular alga. We built a reduced system model of modules to represent the state of an oscillator by using a phase with attractive interactions with others. Because the model is similar to the Kuramoto model, we applied analysis methods. Real robotic modules were built, and experiments were conducted using a colony of the modules. The experimental results confirmed that the colony exhibited stroke synchronization ability by compensating for individual differences. The stroke synchronization is expected to stabilize the movements of robot colonies and improve their overall propulsion.
{"title":"Stroke Synchronization of Underwater Modular Robot through Physical Interaction","authors":"Kohei Nishikawa, Y. Origane, Daisuke Kurabayashi","doi":"10.1109/ROBIO58561.2023.10354986","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354986","url":null,"abstract":"Modular robots are expected to be used in extreme environments owing to their adaptability, and various modular robots have been developed. Most studies have focused on the expandability of capabilities or the integration of modules, whereas only a few studies have investigated autonomous decentralized control, in which each module harmonizes its own movements for overall functionality. We developed an underwater modular robot that synchronizes its paddle strokes; the robot is based on the motif of Gonium, a multicellular alga. We built a reduced system model of modules to represent the state of an oscillator by using a phase with attractive interactions with others. Because the model is similar to the Kuramoto model, we applied analysis methods. Real robotic modules were built, and experiments were conducted using a colony of the modules. The experimental results confirmed that the colony exhibited stroke synchronization ability by compensating for individual differences. The stroke synchronization is expected to stabilize the movements of robot colonies and improve their overall propulsion.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"51 8","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139187224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-04DOI: 10.1109/ROBIO58561.2023.10355037
Aryan Niknam Maleki, Alexander Thompson, M. Runciman, Julia Murray, G. Mylonas
Despite advances in radiotherapy, motion error remains a challenge in prostate radiotherapy. Rectal obturators and endorectal balloons may reduce motion error and improve outcomes but have limitations. We aimed to create a deployable rectal obturator with precise angle control to personalise to a patient’s rectal anatomy, by using an antagonistic pair of "muscle" actuators to flex and extend the device. Results on deployability, angle control, and radial stiffness are presented here. The device can be compressed down to 16 x 3 x 91 mm, and be deployed to maximum dimensions of 24 x 25.5 x 77 mm. The device provides radial stiffness that may be sufficient to stabilise the rectum during radiotherapy. Angle control can be achieved with an average change of 7.5°/ml inflation in the extensor actuator.
尽管放疗技术不断进步，但运动误差仍是前列腺放疗的一大难题。直肠闭塞器和肛门直肠内球囊可减少运动误差并改善治疗效果，但也有局限性。我们的目标是通过使用一对拮抗的 "肌肉 "致动器来弯曲和伸展装置，创造出一种具有精确角度控制功能的可展开直肠闭锁器，以便根据患者的直肠解剖结构进行个性化设计。本文介绍了该装置的可展开性、角度控制和径向刚度结果。该装置可压缩至 16 x 3 x 91 毫米，展开后的最大尺寸为 24 x 25.5 x 77 毫米。该装置提供的径向硬度足以在放疗期间稳定直肠。角度控制可通过伸展致动器 7.5°/ml 的平均充气变化来实现。
{"title":"A soft hydraulic endorectal actuator for prostate radiotherapy","authors":"Aryan Niknam Maleki, Alexander Thompson, M. Runciman, Julia Murray, G. Mylonas","doi":"10.1109/ROBIO58561.2023.10355037","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10355037","url":null,"abstract":"Despite advances in radiotherapy, motion error remains a challenge in prostate radiotherapy. Rectal obturators and endorectal balloons may reduce motion error and improve outcomes but have limitations. We aimed to create a deployable rectal obturator with precise angle control to personalise to a patient’s rectal anatomy, by using an antagonistic pair of \"muscle\" actuators to flex and extend the device. Results on deployability, angle control, and radial stiffness are presented here. The device can be compressed down to 16 x 3 x 91 mm, and be deployed to maximum dimensions of 24 x 25.5 x 77 mm. The device provides radial stiffness that may be sufficient to stabilise the rectum during radiotherapy. Angle control can be achieved with an average change of 7.5°/ml inflation in the extensor actuator.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"49 3","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139187284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-04DOI: 10.1109/ROBIO58561.2023.10354813
Gunjan Gupta, Vedansh Mittal, K. M. Krishna
Visual servoing has been gaining popularity in various real-world vision-centric robotic applications. Autonomous robotic grasping often deals with unseen and unstructured environments, and in this task, Visual Servoing has been able to generate improved end-effector control by providing visual feedback. However, existing Servoing-aided grasping methods tend to fail at the task of grasping in dynamic environments i.e. - moving objects.In this paper, we introduce DynGraspVS, a novel Image-based Visual Servoing-aided Grasping approach that models the motion of moving objects in its interaction matrix. Leveraging a single-step rollout strategy, our approach achieves a remarkable increase in success rate, while converging faster and achieving a smoother trajectory, while maintaining precise alignments in six degrees of freedom. By integrating the velocity information into the interaction matrix, our method is able to successfully complete the challenging task of robotic grasping in the case of dynamic objects, while outperforming existing deep Model Predictive Control (MPC) based methods in the PyBullet simulation environment. We test it with a range of objects in the YCB dataset with varying range of shapes, sizes, and material properties. We report various evaluation metrics such as photometric error, success rate, time taken, and trajectory length.
{"title":"DynGraspVS: Servoing Aided Grasping for Dynamic Environments","authors":"Gunjan Gupta, Vedansh Mittal, K. M. Krishna","doi":"10.1109/ROBIO58561.2023.10354813","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354813","url":null,"abstract":"Visual servoing has been gaining popularity in various real-world vision-centric robotic applications. Autonomous robotic grasping often deals with unseen and unstructured environments, and in this task, Visual Servoing has been able to generate improved end-effector control by providing visual feedback. However, existing Servoing-aided grasping methods tend to fail at the task of grasping in dynamic environments i.e. - moving objects.In this paper, we introduce DynGraspVS, a novel Image-based Visual Servoing-aided Grasping approach that models the motion of moving objects in its interaction matrix. Leveraging a single-step rollout strategy, our approach achieves a remarkable increase in success rate, while converging faster and achieving a smoother trajectory, while maintaining precise alignments in six degrees of freedom. By integrating the velocity information into the interaction matrix, our method is able to successfully complete the challenging task of robotic grasping in the case of dynamic objects, while outperforming existing deep Model Predictive Control (MPC) based methods in the PyBullet simulation environment. We test it with a range of objects in the YCB dataset with varying range of shapes, sizes, and material properties. We report various evaluation metrics such as photometric error, success rate, time taken, and trajectory length.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"37 2","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139187294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-04DOI: 10.1109/ROBIO58561.2023.10354790
Zhaoying Wang, Xu Li, Wenkang Hu
Regular defect inspection of the power line using X-ray is essential for the maintenance of the power line. Usually, conducting such an inspection with a wheeled robot requires dragging the robot from the ground and carefully placing it upon the power line, which is laborious and unsafe. To improve inspection efficiency, the newly developed unmanned aerial vehicle (UAV) provides a promising alternative. However, the positioning error from Global Navigation Satellite System (GNSS) brings the small-scaled drifting movement of the UAV and X-ray camera system, which leads to imaging blur. To cope with this issue, we design a flexible towed aerial robot system to alleviate the instability of the X-ray camera system. Specifically, the UAV and X-ray camera carrier are flexibly connected by a cluster of ropes, reducing the physical impact from the small-scaled drifting movement of the UAV. The permitting position error tolerance between the UAV and the carrier is analyzed. In addition, a guide wheel frame is designed on the carrier to facilitate the carrier’s smooth rolling along the power line. Furthermore, aiming to adapt to the different types of power lines, we design a lightweight motor-driven system to adjust the camera angles and the imaging plate position. Multi-view cameras are also designed to assist the pilot to control the UAV carrying the X-ray camera system landing on the power line. To verify the performance of the developed aerial robot system, we conduct real-world experiments with double bundle conductors and four bundle conductors. The results show that the developed system can efficiently complete inspection. The X-ray camera could obtain a stable imaging condition under the small drifting movement of the flight.
使用 X 射线对电力线进行定期缺陷检查对于维护电力线至关重要。通常情况下，使用轮式机器人进行此类检查需要将机器人从地面拖起，然后小心翼翼地放在电力线上，既费力又不安全。为了提高巡检效率，新开发的无人飞行器（UAV）提供了一个很有前途的替代方案。然而，全球导航卫星系统（GNSS）的定位误差会带来无人飞行器和 X 射线摄像系统的小范围漂移，从而导致成像模糊。为解决这一问题，我们设计了一种灵活的牵引式空中机器人系统，以缓解 X 射线摄像系统的不稳定性。具体来说，无人机和 X 射线照相机载体通过一组绳索柔性连接，减少了无人机小范围漂移带来的物理影响。分析了无人机和载体之间的允许位置误差容限。此外，还在载体上设计了导轮架，以方便载体沿电力线平稳滚动。此外，为了适应不同类型的电力线，我们设计了一种轻型电机驱动系统，用于调整相机角度和成像板位置。我们还设计了多视角摄像头，以协助飞行员控制携带 X 射线摄像系统的无人机在电力线上着陆。为了验证所开发的空中机器人系统的性能，我们对双束导线和四束导线进行了实际实验。结果表明，所开发的系统可以高效地完成检测。X 射线照相机在飞行过程中的微小漂移下也能获得稳定的成像条件。
{"title":"A Flexible Towed Aerial Robot System for Stable X-ray Inspection of Power Lines","authors":"Zhaoying Wang, Xu Li, Wenkang Hu","doi":"10.1109/ROBIO58561.2023.10354790","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354790","url":null,"abstract":"Regular defect inspection of the power line using X-ray is essential for the maintenance of the power line. Usually, conducting such an inspection with a wheeled robot requires dragging the robot from the ground and carefully placing it upon the power line, which is laborious and unsafe. To improve inspection efficiency, the newly developed unmanned aerial vehicle (UAV) provides a promising alternative. However, the positioning error from Global Navigation Satellite System (GNSS) brings the small-scaled drifting movement of the UAV and X-ray camera system, which leads to imaging blur. To cope with this issue, we design a flexible towed aerial robot system to alleviate the instability of the X-ray camera system. Specifically, the UAV and X-ray camera carrier are flexibly connected by a cluster of ropes, reducing the physical impact from the small-scaled drifting movement of the UAV. The permitting position error tolerance between the UAV and the carrier is analyzed. In addition, a guide wheel frame is designed on the carrier to facilitate the carrier’s smooth rolling along the power line. Furthermore, aiming to adapt to the different types of power lines, we design a lightweight motor-driven system to adjust the camera angles and the imaging plate position. Multi-view cameras are also designed to assist the pilot to control the UAV carrying the X-ray camera system landing on the power line. To verify the performance of the developed aerial robot system, we conduct real-world experiments with double bundle conductors and four bundle conductors. The results show that the developed system can efficiently complete inspection. The X-ray camera could obtain a stable imaging condition under the small drifting movement of the flight.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"95 12","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139186822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-04DOI: 10.1109/ROBIO58561.2023.10354962
Yiqi Li, Yelin Jiang, Koh Hosoda
In order to control the motion of a robot, a successful approach is to approximate the robot dynamics as a simplified model. However, the discrepancies between the actual mechanical properties of the robot and the simplified model will result in motion failure for the robot. To address this issue, this paper proposes a pneumatic-driven bipedal musculoskeletal robot that match the mechanistic properties of a simplified spring-loaded inverted pendulum (SLIP) model. The SLIP model is widely applied to robots because it exhibits passive stability and dynamic properties that are similar to human gaits. We designed a musculoskeletal biped robot with its center of mass concentrated in the small body near the hip joint, with low leg inertia based on the properties of the SLIP model. In addition, it it has been verified that the robot exhibits similar characteristics to the SLIP model through a sequential jumping experiment.
{"title":"Spring Loaded Inverted Pendulum Model Based Musculoskeletal Biped Robot Design and Sequential Jumping Experiment","authors":"Yiqi Li, Yelin Jiang, Koh Hosoda","doi":"10.1109/ROBIO58561.2023.10354962","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354962","url":null,"abstract":"In order to control the motion of a robot, a successful approach is to approximate the robot dynamics as a simplified model. However, the discrepancies between the actual mechanical properties of the robot and the simplified model will result in motion failure for the robot. To address this issue, this paper proposes a pneumatic-driven bipedal musculoskeletal robot that match the mechanistic properties of a simplified spring-loaded inverted pendulum (SLIP) model. The SLIP model is widely applied to robots because it exhibits passive stability and dynamic properties that are similar to human gaits. We designed a musculoskeletal biped robot with its center of mass concentrated in the small body near the hip joint, with low leg inertia based on the properties of the SLIP model. In addition, it it has been verified that the robot exhibits similar characteristics to the SLIP model through a sequential jumping experiment.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"94 12","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139186829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-04DOI: 10.1109/ROBIO58561.2023.10355028
Hanne Say, E. Oztop
In continual learning, usually a sequence of tasks are given to a learning agent and the performance of the agent after learning is measured in terms of resistance to catastrophic forgetting, efficacy of knowledge transfer and overall performance on the individual tasks. On the other hand, in multi-task learning, the system is designed to simultaneously acquire knowledge in multiple tasks, often through offline batch learning. A more cognitively valid scenario for lifelong robot learning would be to have a robotic agent to autonomously decide which task to engage and disengage while leveraging many-to-many knowledge transfer ability among tasks during online learning. In this study, we propose a novel lifelong robot learning architecture to fulfill the aforementioned desiderata, and show its validity in an environment where a robot learns the effects of its actions in different task settings. To realize the proposed model, we adopt learning progress measure for task selection, and have the tasks learn by independent neural networks with special structure that allows access to the neural layers of the non-selected tasks. The experiments conducted with a simulated robot arm in an object interaction scenario show that the proposed architecture yields better knowledge transfer and facilitates faster learning compared to baselines of fixed sequence task learning and isolated task learners with no knowledge transfer.
{"title":"A Model for Cognitively Valid Lifelong Learning","authors":"Hanne Say, E. Oztop","doi":"10.1109/ROBIO58561.2023.10355028","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10355028","url":null,"abstract":"In continual learning, usually a sequence of tasks are given to a learning agent and the performance of the agent after learning is measured in terms of resistance to catastrophic forgetting, efficacy of knowledge transfer and overall performance on the individual tasks. On the other hand, in multi-task learning, the system is designed to simultaneously acquire knowledge in multiple tasks, often through offline batch learning. A more cognitively valid scenario for lifelong robot learning would be to have a robotic agent to autonomously decide which task to engage and disengage while leveraging many-to-many knowledge transfer ability among tasks during online learning. In this study, we propose a novel lifelong robot learning architecture to fulfill the aforementioned desiderata, and show its validity in an environment where a robot learns the effects of its actions in different task settings. To realize the proposed model, we adopt learning progress measure for task selection, and have the tasks learn by independent neural networks with special structure that allows access to the neural layers of the non-selected tasks. The experiments conducted with a simulated robot arm in an object interaction scenario show that the proposed architecture yields better knowledge transfer and facilitates faster learning compared to baselines of fixed sequence task learning and isolated task learners with no knowledge transfer.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"83 8","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139186865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-04DOI: 10.1109/ROBIO58561.2023.10354777
Zhenzhen Tan, Wangjie Zhou, Jie Chen, Yang Xian, Quan Zhang, Long Li, Tao Yue, Yingzhong Tian, Sicheng Yi
This paper studies the stabilization control of underactuated Unmanned Surface Vehicles (USV). Firstly, a three-degree-of-freedom (3-DOF) of underactuated USV in complex sea conditions is established. On this basis, a backstepping sliding mode stability controller based on disturbance observer (BSMC-NDC) for USV is designed. The backstepping sliding mode control strategy is used to achieve the stabilization control effect, and the hyperbolic tangent continuous sliding mode is used to reduce the controller jitter. Aiming at the complicated ocean disturbance in the process of USV stabilization, a 3-DOF disturbance observer based on exponential convergence is designed. The effectiveness of the control system is fully verfied by comparing the simulation results of similar controllers. Specifically, simulation results show that the proposed controller can achieve the USV stabilization control and solve the jitter problem in the sliding mode control process.
{"title":"Backstepping sliding mode stabilization controller for underactuated unmanned surface vehicle based on disturbance observer","authors":"Zhenzhen Tan, Wangjie Zhou, Jie Chen, Yang Xian, Quan Zhang, Long Li, Tao Yue, Yingzhong Tian, Sicheng Yi","doi":"10.1109/ROBIO58561.2023.10354777","DOIUrl":"https://doi.org/10.1109/ROBIO58561.2023.10354777","url":null,"abstract":"This paper studies the stabilization control of underactuated Unmanned Surface Vehicles (USV). Firstly, a three-degree-of-freedom (3-DOF) of underactuated USV in complex sea conditions is established. On this basis, a backstepping sliding mode stability controller based on disturbance observer (BSMC-NDC) for USV is designed. The backstepping sliding mode control strategy is used to achieve the stabilization control effect, and the hyperbolic tangent continuous sliding mode is used to reduce the controller jitter. Aiming at the complicated ocean disturbance in the process of USV stabilization, a 3-DOF disturbance observer based on exponential convergence is designed. The effectiveness of the control system is fully verfied by comparing the simulation results of similar controllers. Specifically, simulation results show that the proposed controller can achieve the USV stabilization control and solve the jitter problem in the sliding mode control process.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"103 10","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139186893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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