Pub Date : 2022-05-23DOI: 10.1109/icra46639.2022.9812227
Guilhem Buisan, Anthony Favier, Amandine Mayima, R. Alami
The variety and complexity of tasks autonomous robots can tackle is constantly increasing, yet we seldom see robots collaborating with humans. Indeed, humans are either requested for punctual help or are given the lead on the whole task. We propose a human-aware task planning approach allowing the robot to plan for a task while also considering and emulating the human decision, action, and reaction processes. Our approach, named Human-Aware Task Planner with Emulation of Human Decisions and Actions (HATP/EHDA), is based on the exploration of multiple hierarchical tasks networks albeit differently whether the agent is considered to be controllable (the robot) or uncontrollable (the human). We present the rationale of our approach along with a formalization and show its potential on an illustrative example.
{"title":"HATP/EHDA: A Robot Task Planner Anticipating and Eliciting Human Decisions and Actions","authors":"Guilhem Buisan, Anthony Favier, Amandine Mayima, R. Alami","doi":"10.1109/icra46639.2022.9812227","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9812227","url":null,"abstract":"The variety and complexity of tasks autonomous robots can tackle is constantly increasing, yet we seldom see robots collaborating with humans. Indeed, humans are either requested for punctual help or are given the lead on the whole task. We propose a human-aware task planning approach allowing the robot to plan for a task while also considering and emulating the human decision, action, and reaction processes. Our approach, named Human-Aware Task Planner with Emulation of Human Decisions and Actions (HATP/EHDA), is based on the exploration of multiple hierarchical tasks networks albeit differently whether the agent is considered to be controllable (the robot) or uncontrollable (the human). We present the rationale of our approach along with a formalization and show its potential on an illustrative example.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132407147","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 : 2022-05-23DOI: 10.1109/icra46639.2022.9811640
Shaohang Xu, Lijun Zhu, C. Ho
Four-legged animals are able to change their gaits adaptively for lower energy consumption. However, designing a robust controller for their robot counterparts with multi-modal locomotion remains challenging. In this paper, we present a hierarchical control framework that decomposes this challenge into two kinds of problems: high-level decision-making for gait selection and robust low-level control in complex application environments. For gait transitions, we use reinforcement learning (RL) to design a gait policy that selects the optimal gaits in different environments. After the gait is decided, model predictive control (MPC) is applied to implement the desired gait. To improve the robustness of the locomotion, a model adaptation policy is developed to optimize the input parameters of our MPC controller adaptively. The control framework is first trained and tested in simulation, and then it is applied directly to a quadruped robot in real without any fine-tuning. We show that our control framework is more energy efficient by choosing different gaits and is more robust by adjusting model parameters compared to baseline controllers.
{"title":"Learning Efficient and Robust Multi-Modal Quadruped Locomotion: A Hierarchical Approach","authors":"Shaohang Xu, Lijun Zhu, C. Ho","doi":"10.1109/icra46639.2022.9811640","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9811640","url":null,"abstract":"Four-legged animals are able to change their gaits adaptively for lower energy consumption. However, designing a robust controller for their robot counterparts with multi-modal locomotion remains challenging. In this paper, we present a hierarchical control framework that decomposes this challenge into two kinds of problems: high-level decision-making for gait selection and robust low-level control in complex application environments. For gait transitions, we use reinforcement learning (RL) to design a gait policy that selects the optimal gaits in different environments. After the gait is decided, model predictive control (MPC) is applied to implement the desired gait. To improve the robustness of the locomotion, a model adaptation policy is developed to optimize the input parameters of our MPC controller adaptively. The control framework is first trained and tested in simulation, and then it is applied directly to a quadruped robot in real without any fine-tuning. We show that our control framework is more energy efficient by choosing different gaits and is more robust by adjusting model parameters compared to baseline controllers.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133893170","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 : 2022-05-23DOI: 10.1109/icra46639.2022.9811711
Alexander Stumpf, O. Stryk
In recent years, the capabilities of legged locomotion controllers have been significantly advanced enabling them to traverse basic types of uneven terrain without visual perception. However, safely and autonomously traversing longer distances over difficult uneven terrain requires appropriate motion planning using online collected environmental knowledge. In this paper, we present such a novel methodology for generic closed-loop preceding horizon footstep planning that enables legged robots equipped with capable locomotion controllers to autonomously traverse previously unknown terrain while continuously walking long distances. Hereby, our approach addresses the challenge of online terrain perception and soft real-time footstep planning. The proposed new formulation of the search-based planning problem makes no specific assumptions about the robot kinematics (e.g. number of legs) or the used locomotion control schemes. Therefore, it can be applied to a broad range of different types of legged robots. Unlike current methods, the proposed new framework can optionally consider the floating base as part of the state-space. It is possible to configure the complexity of the planner online, from efficiently solving tasks in flat terrain to using non-contiguous contacts in highly challenging terrain. Finally, the presented methodology is successfully applied and evaluated in virtual and real experiments on state of the art bipedal, quadrupedal, and a novel eight-legged robot.
{"title":"A Universal Footstep Planning Methodology for Continuous Walking in Challenging Terrain Applicable to Different Types of Legged Robots","authors":"Alexander Stumpf, O. Stryk","doi":"10.1109/icra46639.2022.9811711","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9811711","url":null,"abstract":"In recent years, the capabilities of legged locomotion controllers have been significantly advanced enabling them to traverse basic types of uneven terrain without visual perception. However, safely and autonomously traversing longer distances over difficult uneven terrain requires appropriate motion planning using online collected environmental knowledge. In this paper, we present such a novel methodology for generic closed-loop preceding horizon footstep planning that enables legged robots equipped with capable locomotion controllers to autonomously traverse previously unknown terrain while continuously walking long distances. Hereby, our approach addresses the challenge of online terrain perception and soft real-time footstep planning. The proposed new formulation of the search-based planning problem makes no specific assumptions about the robot kinematics (e.g. number of legs) or the used locomotion control schemes. Therefore, it can be applied to a broad range of different types of legged robots. Unlike current methods, the proposed new framework can optionally consider the floating base as part of the state-space. It is possible to configure the complexity of the planner online, from efficiently solving tasks in flat terrain to using non-contiguous contacts in highly challenging terrain. Finally, the presented methodology is successfully applied and evaluated in virtual and real experiments on state of the art bipedal, quadrupedal, and a novel eight-legged robot.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134146603","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 : 2022-05-23DOI: 10.1109/icra46639.2022.9811790
Yeting Liu, Junjie Shen, Jingwen Zhang, Xiaoguang Zhang, Taoyuanmin Zhu, D. Hong
As the study of humanoid robots becomes a world-wide interdisciplinary research field, the demand for a cost-effective bipedal robot system capable of dynamic behaviors is growing exponentially. This paper presents a miniature bipedal robot named Bipedal Robot Unit with Compliance Enhanced (BRUCE). Each leg of BRUCE has five degrees of freedom (DoFs), which includes a spherical hip joint, a knee joint, and an ankle joint. To lower the leg inertia, a cable-driven differential pulley system and a linkage mechanism are applied to the hip and ankle joints, respectively. With the proposed design, BRUCE is able to achieve a similar range of motion to a human's lower body. The proprioceptive actuation and contact sensing further prepare BRUCE for interactions with unstructured environments. For real-time control of dynamic motions, a convex formulation for model hierarchy predictive control (MHPC) is introduced. MHPC plans with whole-body dynamics in the near horizon and simplified dynamics in the long horizon to benefit from both model accuracy and computational efficiency. A series of experiments were conducted to evaluate the overall system performance including hip joint analysis, walking, push recovery, and vertical jumping.
{"title":"Design and Control of a Miniature Bipedal Robot with Proprioceptive Actuation for Dynamic Behaviors","authors":"Yeting Liu, Junjie Shen, Jingwen Zhang, Xiaoguang Zhang, Taoyuanmin Zhu, D. Hong","doi":"10.1109/icra46639.2022.9811790","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9811790","url":null,"abstract":"As the study of humanoid robots becomes a world-wide interdisciplinary research field, the demand for a cost-effective bipedal robot system capable of dynamic behaviors is growing exponentially. This paper presents a miniature bipedal robot named Bipedal Robot Unit with Compliance Enhanced (BRUCE). Each leg of BRUCE has five degrees of freedom (DoFs), which includes a spherical hip joint, a knee joint, and an ankle joint. To lower the leg inertia, a cable-driven differential pulley system and a linkage mechanism are applied to the hip and ankle joints, respectively. With the proposed design, BRUCE is able to achieve a similar range of motion to a human's lower body. The proprioceptive actuation and contact sensing further prepare BRUCE for interactions with unstructured environments. For real-time control of dynamic motions, a convex formulation for model hierarchy predictive control (MHPC) is introduced. MHPC plans with whole-body dynamics in the near horizon and simplified dynamics in the long horizon to benefit from both model accuracy and computational efficiency. A series of experiments were conducted to evaluate the overall system performance including hip joint analysis, walking, push recovery, and vertical jumping.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134293203","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 : 2022-05-23DOI: 10.1109/icra46639.2022.9812246
Guanqiao Shan, Zhuoran Zhang, C. Dai, Hang Liu, Xian Wang, Wenkun Dou, Yu Sun
Soft tissue cutting is used for incision, separation and removal of tissues or cells. Due to high deformation of soft tissues resulting from their viscosity and elasticity, it is challenging to accurately cut the tissue along a desired path and control the force applied to the tissue for reducing invasiveness, especially at the microscale. This paper presents a robotic biopsy system for cutting and collecting trophectoderm cells from a highly deformable blastocyst. The system, for the first time, enables TE cell junction detection for laser ablation throughout the blastocyst biopsy process by using a convolutional neural network. The overall detection error was 2.13% in every 1,000 cell junctions with position RMSE of $1.63 mu mathrm{m}pm 0.29 mu mathrm{m}$. A dynamics model was developed to describe the motion of the trophectoderm cells inside a biopsy micropipette. Based on this model, an adaptive control method was developed for trophectoderm cell aspiration and positioning inside the biopsy micropipette. Experimental results revealed that the controller was capable of effectively compensating for the cell positioning error by updating the varying system parameters according to the adaptation law. The success rate was 100%, the cell aggregate positioning accuracy was $pm 1 mu mathrm{m}$, the average settling time was 2 s, and the largest overshoot was $4.3 mu mathrm{m}$. Compared to manual blastocyst biopsy, the robotic biopsy system shortened the blastocyst's recovery time (35 min vs. 50 min) which indicates lower invasiveness.
软组织切割是用于切开、分离和去除组织或细胞。由于软组织的粘性和弹性导致其高度变形，因此沿着所需的路径精确切割组织并控制施加在组织上的力以减少侵入性是具有挑战性的，特别是在微观尺度下。本文介绍了一种机器人活检系统，用于从高度变形的囊胚中切割和收集滋养外胚层细胞。该系统首次使用卷积神经网络，在整个囊胚活检过程中实现激光消融的TE细胞结检测。每1000个细胞连接的总体检测误差为2.13%，位置RMSE为$1.63 mu mathm {m}pm 0.29 mu mathm {m}$。建立了一个动力学模型来描述活组织检查微移液管中滋养外胚层细胞的运动。基于该模型，提出了一种滋养外胚层细胞在活检微管内吸出定位的自适应控制方法。实验结果表明，该控制器能够根据自适应规律更新系统参数，有效补偿单元定位误差。成功率为100%，单元群定位精度为$pm 1 mu mathrm{m}$，平均沉降时间为2s，最大超调值为$4.3 mu mathrm{m}$。与人工囊胚活检相比，机器人活检系统缩短了囊胚的恢复时间(35分钟对50分钟)，这表明侵入性更低。
{"title":"Robotic Cell Manipulation for Blastocyst Biopsy","authors":"Guanqiao Shan, Zhuoran Zhang, C. Dai, Hang Liu, Xian Wang, Wenkun Dou, Yu Sun","doi":"10.1109/icra46639.2022.9812246","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9812246","url":null,"abstract":"Soft tissue cutting is used for incision, separation and removal of tissues or cells. Due to high deformation of soft tissues resulting from their viscosity and elasticity, it is challenging to accurately cut the tissue along a desired path and control the force applied to the tissue for reducing invasiveness, especially at the microscale. This paper presents a robotic biopsy system for cutting and collecting trophectoderm cells from a highly deformable blastocyst. The system, for the first time, enables TE cell junction detection for laser ablation throughout the blastocyst biopsy process by using a convolutional neural network. The overall detection error was 2.13% in every 1,000 cell junctions with position RMSE of $1.63 mu mathrm{m}pm 0.29 mu mathrm{m}$. A dynamics model was developed to describe the motion of the trophectoderm cells inside a biopsy micropipette. Based on this model, an adaptive control method was developed for trophectoderm cell aspiration and positioning inside the biopsy micropipette. Experimental results revealed that the controller was capable of effectively compensating for the cell positioning error by updating the varying system parameters according to the adaptation law. The success rate was 100%, the cell aggregate positioning accuracy was $pm 1 mu mathrm{m}$, the average settling time was 2 s, and the largest overshoot was $4.3 mu mathrm{m}$. Compared to manual blastocyst biopsy, the robotic biopsy system shortened the blastocyst's recovery time (35 min vs. 50 min) which indicates lower invasiveness.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130755432","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 : 2022-05-23DOI: 10.1109/icra46639.2022.9811717
Jacob Higgins, N. Bezzo
Agile navigation through uncertain and obstacle-rich environments remains a challenging task for autonomous mobile robots (AMR). For most AMR, obstacles are identified using onboard sensors, e.g., lidar or cameras. The effectiveness of these sensors may be severely limited, however, by occlusions introduced from the presence of other obstacles. The occluded area may contain obstacles, static or dynamic, not included into the motion planning of the robot and could cause potential collisions if they suddenly appear in the field of view of the robot. This paper proposes a general Model Predictive Control (MPC)-based framework for handling occlusions in structured or unstructured environments, that contain known or unknown static or dynamic obstacles. Safety is promoted by commanding velocities that consider surrounding obstacle uncertainty, while perception is promoted through a specially designed objective that can reduce the occluded area created by obstacles. The effectiveness of this framework is validated through simulations that show swift and safe motion in a variety of different environments. Similarly, experimental validation is achieved with a Boston Dynamics' Spot quadruped robot operating in an occluding environment.
{"title":"A Model Predictive-based Motion Planning Method for Safe and Agile Traversal of Unknown and Occluding Environments","authors":"Jacob Higgins, N. Bezzo","doi":"10.1109/icra46639.2022.9811717","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9811717","url":null,"abstract":"Agile navigation through uncertain and obstacle-rich environments remains a challenging task for autonomous mobile robots (AMR). For most AMR, obstacles are identified using onboard sensors, e.g., lidar or cameras. The effectiveness of these sensors may be severely limited, however, by occlusions introduced from the presence of other obstacles. The occluded area may contain obstacles, static or dynamic, not included into the motion planning of the robot and could cause potential collisions if they suddenly appear in the field of view of the robot. This paper proposes a general Model Predictive Control (MPC)-based framework for handling occlusions in structured or unstructured environments, that contain known or unknown static or dynamic obstacles. Safety is promoted by commanding velocities that consider surrounding obstacle uncertainty, while perception is promoted through a specially designed objective that can reduce the occluded area created by obstacles. The effectiveness of this framework is validated through simulations that show swift and safe motion in a variety of different environments. Similarly, experimental validation is achieved with a Boston Dynamics' Spot quadruped robot operating in an occluding environment.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130892310","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 : 2022-05-23DOI: 10.1109/icra46639.2022.9812199
Adwait Mane, Dylan Swart, J. White, Christian M. Hubicki
Tracks, wheels, and legs are all useful locomotion modes for Unmanned Ground Vehicles (UGVs), and ground robots that combine these mechanisms have the potential to climb over large obstacles. As robot morphologies include more degrees of freedom and obstacles become increasingly large and complex, UGVs will need to rely on automatic motion planning to compute the joint trajectories for traversal. This article presents a trajectory optimization formulation for multibody UGVs with combined wheel-leg and track-leg designs. We derive the dynamics and constraints for rolling wheels and circulating elliptical tracks. Using direct collocation, we formulate a model-based trajectory optimization where all constraints and objectives are written in closed-form with smooth and exact derivatives for tractable computation times with existing large-scale nonlinear optimization solvers (<1 minute). We demonstrate the trajectory optimization on numerous simulated planar wheel-leg and track-leg morphologies completing locomotion tasks, demonstrating full body dynamic coupling for the multibody system. Future work will extend this formulation to 3D and include contact planning.
{"title":"Trajectory Optimization Formulation with Smooth Analytical Derivatives for Track-leg and Wheel-leg Ground Robots","authors":"Adwait Mane, Dylan Swart, J. White, Christian M. Hubicki","doi":"10.1109/icra46639.2022.9812199","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9812199","url":null,"abstract":"Tracks, wheels, and legs are all useful locomotion modes for Unmanned Ground Vehicles (UGVs), and ground robots that combine these mechanisms have the potential to climb over large obstacles. As robot morphologies include more degrees of freedom and obstacles become increasingly large and complex, UGVs will need to rely on automatic motion planning to compute the joint trajectories for traversal. This article presents a trajectory optimization formulation for multibody UGVs with combined wheel-leg and track-leg designs. We derive the dynamics and constraints for rolling wheels and circulating elliptical tracks. Using direct collocation, we formulate a model-based trajectory optimization where all constraints and objectives are written in closed-form with smooth and exact derivatives for tractable computation times with existing large-scale nonlinear optimization solvers (<1 minute). We demonstrate the trajectory optimization on numerous simulated planar wheel-leg and track-leg morphologies completing locomotion tasks, demonstrating full body dynamic coupling for the multibody system. Future work will extend this formulation to 3D and include contact planning.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131219490","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 : 2022-05-23DOI: 10.1109/icra46639.2022.9812217
Dong Wei, Shan An, Xiajie Zhang, Jiayi Tian, Konstantinos A. Tsintotas, A. Gasteratos, Haogang Zhu
Hand pose estimation constitutes prime attainment for human-machine interaction-based applications. Real-time operation is vital in such tasks. Thus, a reliable estimator should exhibit low computational complexity and high precision at the same time. Previous works have explored the regression techniques, including the coordinate regression and heatmap regression methods. Primarily incorporating ideas from them, in this paper, we propose a novel, fast and accurate method for hand pose estimation, which adopts a lightweight network architecture and a post-processing scheme. Hence, our architecture uses a Dual Regression strategy, consisting of two regression branches, namely the coordinate and the heatmap ones, and we refer to the proposed method as DRHand. By carefully selecting the branches' characteristics, the proposed structure has been designed to exploit the benefits of the two methods mentioned above while impoverishing their weaknesses to some extent. The two branches are supervised separately during training, and a post-processing module estimates their outputs to boost reliability. This way, our novel pipeline is considerably faster, reaching 44.39 frames-per-second on an NVIDIA Jetson TX2 graphics processing unit, offering a beyond real-time performance for any custom robotics application. Lastly, extensive experiments conducted on two publicly-available datasets demonstrate that the proposed framework outperforms previous state-of-the-art techniques and can generalize on various hand pose scenarios.
{"title":"Dual Regression for Efficient Hand Pose Estimation","authors":"Dong Wei, Shan An, Xiajie Zhang, Jiayi Tian, Konstantinos A. Tsintotas, A. Gasteratos, Haogang Zhu","doi":"10.1109/icra46639.2022.9812217","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9812217","url":null,"abstract":"Hand pose estimation constitutes prime attainment for human-machine interaction-based applications. Real-time operation is vital in such tasks. Thus, a reliable estimator should exhibit low computational complexity and high precision at the same time. Previous works have explored the regression techniques, including the coordinate regression and heatmap regression methods. Primarily incorporating ideas from them, in this paper, we propose a novel, fast and accurate method for hand pose estimation, which adopts a lightweight network architecture and a post-processing scheme. Hence, our architecture uses a Dual Regression strategy, consisting of two regression branches, namely the coordinate and the heatmap ones, and we refer to the proposed method as DRHand. By carefully selecting the branches' characteristics, the proposed structure has been designed to exploit the benefits of the two methods mentioned above while impoverishing their weaknesses to some extent. The two branches are supervised separately during training, and a post-processing module estimates their outputs to boost reliability. This way, our novel pipeline is considerably faster, reaching 44.39 frames-per-second on an NVIDIA Jetson TX2 graphics processing unit, offering a beyond real-time performance for any custom robotics application. Lastly, extensive experiments conducted on two publicly-available datasets demonstrate that the proposed framework outperforms previous state-of-the-art techniques and can generalize on various hand pose scenarios.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132046521","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 : 2022-05-23DOI: 10.1109/icra46639.2022.9811694
Choong-Keun Lee, Taeyoon Lee, Jae-Kyung Min, Albert Wang, SungPyo Lee, Jaesung Oh, Chang-Woo Park, Keunjun Choi
Manipulation involves a broad spectrum of skills, e.g., polishing, peeling, flipping, screwing, etc., requiring complex and delicate control over both force and position. This paper aims at designing an optimal haptic interface for providing a robot with direct demonstrations of human's innate intelligence in performing a wide range of force-based bimanual manipulation tasks. Based on the proprioceptive actuation mechanism, kinodynamic design parameters of the (dual) 7-DOF haptic arm are optimized so as to maximize the force transparency perceived by the operator over the full real-scale workspace of human arm while also ensuring other important constraints including robot-to-operator collision and singularity avoidance, payload, controlled stiffness, etc. 2.65 kg of average reflective mass and 1500 N/m of controlled stiffness is achieved over the entire workspace. We show the efficacy of our haptic interface by demonstrating various force-based manipulation tasks with a light-weight anthropomorphic bimanual manipulator, LIMS2-AMBIDEX [1].
{"title":"A Proprioceptive Haptic Device Design for Teaching Bimanual Manipulation","authors":"Choong-Keun Lee, Taeyoon Lee, Jae-Kyung Min, Albert Wang, SungPyo Lee, Jaesung Oh, Chang-Woo Park, Keunjun Choi","doi":"10.1109/icra46639.2022.9811694","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9811694","url":null,"abstract":"Manipulation involves a broad spectrum of skills, e.g., polishing, peeling, flipping, screwing, etc., requiring complex and delicate control over both force and position. This paper aims at designing an optimal haptic interface for providing a robot with direct demonstrations of human's innate intelligence in performing a wide range of force-based bimanual manipulation tasks. Based on the proprioceptive actuation mechanism, kinodynamic design parameters of the (dual) 7-DOF haptic arm are optimized so as to maximize the force transparency perceived by the operator over the full real-scale workspace of human arm while also ensuring other important constraints including robot-to-operator collision and singularity avoidance, payload, controlled stiffness, etc. 2.65 kg of average reflective mass and 1500 N/m of controlled stiffness is achieved over the entire workspace. We show the efficacy of our haptic interface by demonstrating various force-based manipulation tasks with a light-weight anthropomorphic bimanual manipulator, LIMS2-AMBIDEX [1].","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132439297","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 : 2022-05-23DOI: 10.1109/icra46639.2022.9811731
Jixiu Li, Zhang Tao, T. Cheng, Yehui Li, Heng Zhang, Yisen Huang, C. Ng, P. Chiu, Zheng Li
This paper presents a long-range magnetic actuated and guided endoscope for uniport video-assisted thoracic surgery (VATS). In VATS, the incision is quite narrow and part of the chest wall may be very thick. So, the magnetic endoscope system is required to produce sufficient attractive force at a considerable distance with a compact dimension. In this paper, a magnetic endoscope system is developed to meet the aforementioned clinical demands. In the system, both the internal and external units consist of two cylindrical magnets at both ends and a semi-cylindrical magnet in the middle. Coupled with the magnetic field from the external unit, the internal endoscope can achieve anchoring, tilting, panning, and translating to provide the desired view for the surgeon. The rotation of the endoscope is dynamically modeled by combining magnetic theory and coordinate transformation. The prototype is made with a boundary box of 10×14×56 mm, which can be inserted through the narrow incision in VATS. In the experiment, the developed models of anchoring, tilting, and panning were verified. The magnet configuration in the system can achieve a static anchoring distance of 95 mm and exhibits enhancement in attractive force compared with other designs.
{"title":"Design and Analysis of a Long-range Magnetic Actuated and Guided Endoscope for Uniport VATS","authors":"Jixiu Li, Zhang Tao, T. Cheng, Yehui Li, Heng Zhang, Yisen Huang, C. Ng, P. Chiu, Zheng Li","doi":"10.1109/icra46639.2022.9811731","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9811731","url":null,"abstract":"This paper presents a long-range magnetic actuated and guided endoscope for uniport video-assisted thoracic surgery (VATS). In VATS, the incision is quite narrow and part of the chest wall may be very thick. So, the magnetic endoscope system is required to produce sufficient attractive force at a considerable distance with a compact dimension. In this paper, a magnetic endoscope system is developed to meet the aforementioned clinical demands. In the system, both the internal and external units consist of two cylindrical magnets at both ends and a semi-cylindrical magnet in the middle. Coupled with the magnetic field from the external unit, the internal endoscope can achieve anchoring, tilting, panning, and translating to provide the desired view for the surgeon. The rotation of the endoscope is dynamically modeled by combining magnetic theory and coordinate transformation. The prototype is made with a boundary box of 10×14×56 mm, which can be inserted through the narrow incision in VATS. In the experiment, the developed models of anchoring, tilting, and panning were verified. The magnet configuration in the system can achieve a static anchoring distance of 95 mm and exhibits enhancement in attractive force compared with other designs.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132572601","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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