Pub Date : 2022-05-23DOI: 10.1109/icra46639.2022.9812324
Clark B. Teeple, Justin Werfel, R. Wood
In this paper, we discuss the role of gripper compliance in successful grasping and manipulation of thin, flexible materials. We show, both conceptually and empirically, that each axis of compliance in a planar gripper provides unique benefits in this domain. Vertical compliance allows robust grasping of thin materials in the presence of large uncertainty in positioning. Lateral compliance increases opportunity to respond to unexpected snags by increasing the time window over which tensile forces are applied. Rotational compliance avoids damage to objects by decreasing the maximum tensile forces applied during snags. We explore these three benefits through empirical tests comparing a rigid gripper to a soft gripper, evaluating the level of vertical uncertainty each can handle for prehensile and non-prehensile manipulation, as well as the forces and displacements incurred during snags. The results show how a soft gripper's three-axis compliance provides a passive ability to prevent damage to delicate materials.
{"title":"Multi-Dimensional Compliance of Soft Grippers Enables Gentle Interaction with Thin, Flexible Objects","authors":"Clark B. Teeple, Justin Werfel, R. Wood","doi":"10.1109/icra46639.2022.9812324","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9812324","url":null,"abstract":"In this paper, we discuss the role of gripper compliance in successful grasping and manipulation of thin, flexible materials. We show, both conceptually and empirically, that each axis of compliance in a planar gripper provides unique benefits in this domain. Vertical compliance allows robust grasping of thin materials in the presence of large uncertainty in positioning. Lateral compliance increases opportunity to respond to unexpected snags by increasing the time window over which tensile forces are applied. Rotational compliance avoids damage to objects by decreasing the maximum tensile forces applied during snags. We explore these three benefits through empirical tests comparing a rigid gripper to a soft gripper, evaluating the level of vertical uncertainty each can handle for prehensile and non-prehensile manipulation, as well as the forces and displacements incurred during snags. The results show how a soft gripper's three-axis compliance provides a passive ability to prevent damage to delicate materials.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"23 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":"132757005","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/icra46639.2022.9811825
Bukeikhan Omarali, Francesca Palermo, K. Althoefer, Maurizio Valle, I. Farkhatdinov
This work presents a method for tactile classification of materials for virtual reality (VR) based robot teleoperation. In our system, a human-operator uses a remotely controlled robot-manipulator with an optical fibre-based tactile and proximity sensor to scan surfaces of objects in a remote environment. Tactile and proximity data and the robot's end-effector state feedback are used for the classification of objects' materials which are then visualized in the VR reconstruction of the remote environment for each object. Machine learning techniques such as random forest, convolutional neural and multi-modal convolutional neural networks were used for material classification. The proposed system and methods were tested with five different materials and classification accuracy of 90 % and more was achieved. The results of material classification were successfully exploited for visualising the remote scene in the VR interface to provide more information to the human-operator.
{"title":"Tactile Classification of Object Materials for Virtual Reality based Robot Teleoperation","authors":"Bukeikhan Omarali, Francesca Palermo, K. Althoefer, Maurizio Valle, I. Farkhatdinov","doi":"10.1109/icra46639.2022.9811825","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9811825","url":null,"abstract":"This work presents a method for tactile classification of materials for virtual reality (VR) based robot teleoperation. In our system, a human-operator uses a remotely controlled robot-manipulator with an optical fibre-based tactile and proximity sensor to scan surfaces of objects in a remote environment. Tactile and proximity data and the robot's end-effector state feedback are used for the classification of objects' materials which are then visualized in the VR reconstruction of the remote environment for each object. Machine learning techniques such as random forest, convolutional neural and multi-modal convolutional neural networks were used for material classification. The proposed system and methods were tested with five different materials and classification accuracy of 90 % and more was achieved. The results of material classification were successfully exploited for visualising the remote scene in the VR interface to provide more information to the human-operator.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"21 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":"131403515","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/icra46639.2022.9811787
R. Sukhnandan, Kevin Dai, Victoria A. Webster-Wood
Damping properties in biological muscle are crit-ical for absorbing shock, maintaining posture, and positioning limbs and appendages. When creating biomimetic robots, the ability to replicate the dynamics of biological muscle is neces-sary to reproduce behaviors seen in an animal model. However, the damping properties of existing soft artificial muscles are difficult to predict and tune to match specific muscles as may be needed in biomimetic robots. Here, we present the design, manufacturing, and characterization of a novel soft damper to enable a greater degree of biomimetism in these soft actuators. The damper is composed of magnetorheological fluid contained within an elastomeric shell, which is cast using low-cost 3D printed parts and commercially available urethane rubber. We demonstrate that the force-velocity response over a velocity range of 0.1 to 10 mm/s is proportional to applied magnetic flux densities between 0.12 and 0.31 T. In the presence of a 0.31 T magnetic field from a small permanent magnet, the damper is capable of a maximum damping force increase of 13.2 N to 15.5 N relative to the 0 T control, at a compression depth of 7.9 mm, which is larger than that of several previously reported centimeter-scale dampers. As a proof-of-concept for integration with a Pneumatic Artificial Muscle (PAM), we use two parallel dampers to reduce the oscillations of a rapidly pressurized McKibben actuator. The ability to modulate the force-velocity performance of our elastomeric damper paves the way for custom damping profiles that can be used to improve biomimetism in soft robotic actuators.
{"title":"A Magnetorheological Fluid-based Damper Towards Increased Biomimetism in Soft Robotic Actuators*","authors":"R. Sukhnandan, Kevin Dai, Victoria A. Webster-Wood","doi":"10.1109/icra46639.2022.9811787","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9811787","url":null,"abstract":"Damping properties in biological muscle are crit-ical for absorbing shock, maintaining posture, and positioning limbs and appendages. When creating biomimetic robots, the ability to replicate the dynamics of biological muscle is neces-sary to reproduce behaviors seen in an animal model. However, the damping properties of existing soft artificial muscles are difficult to predict and tune to match specific muscles as may be needed in biomimetic robots. Here, we present the design, manufacturing, and characterization of a novel soft damper to enable a greater degree of biomimetism in these soft actuators. The damper is composed of magnetorheological fluid contained within an elastomeric shell, which is cast using low-cost 3D printed parts and commercially available urethane rubber. We demonstrate that the force-velocity response over a velocity range of 0.1 to 10 mm/s is proportional to applied magnetic flux densities between 0.12 and 0.31 T. In the presence of a 0.31 T magnetic field from a small permanent magnet, the damper is capable of a maximum damping force increase of 13.2 N to 15.5 N relative to the 0 T control, at a compression depth of 7.9 mm, which is larger than that of several previously reported centimeter-scale dampers. As a proof-of-concept for integration with a Pneumatic Artificial Muscle (PAM), we use two parallel dampers to reduce the oscillations of a rapidly pressurized McKibben actuator. The ability to modulate the force-velocity performance of our elastomeric damper paves the way for custom damping profiles that can be used to improve biomimetism in soft robotic actuators.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"55 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":"115708636","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/icra46639.2022.9812338
Jian Di, Shaofeng Chen, Xinghu Wang, Hepeng Zhang, H. Ji
Insulator visual aiming is difficult for washing drone due to the complex washing environment, strong dis-turbance, lack of debugging environment, and other factors. Conventional visual servo control methods often fail to consider these complex factors adequately and fall short in reliable insulator visual aiming. To address these problems, we propose a novel multi-feature fusion-based drone visual servo control method for accurate insulator visual aiming. A multi-feature fusion neural network (MFFNet) is proposed to map the dif-ferent input modalities into an embedding space spanned by the learned deep features. Suitable control commands are generated by the simple combination of learned deep features. These deep features represent the intrinsic structural properties of the insulator and the motion pattern of the drones. Particularly, our method is trained purely in simulation and transferred to a real drone directly. Moreover, accurate visual aiming is guaranteed even in strong disturbance environments. Simulation and experimental results verify the high accurate insulator aiming, anti-disturbance, and sim-to-real transfer capabilities of the proposed method. Video: https://youtu.be/Ptlajzvp46A.
{"title":"Insulator Aiming Using Multi-Feature Fusion-Based Visual Servo Control for Washing Drone","authors":"Jian Di, Shaofeng Chen, Xinghu Wang, Hepeng Zhang, H. Ji","doi":"10.1109/icra46639.2022.9812338","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9812338","url":null,"abstract":"Insulator visual aiming is difficult for washing drone due to the complex washing environment, strong dis-turbance, lack of debugging environment, and other factors. Conventional visual servo control methods often fail to consider these complex factors adequately and fall short in reliable insulator visual aiming. To address these problems, we propose a novel multi-feature fusion-based drone visual servo control method for accurate insulator visual aiming. A multi-feature fusion neural network (MFFNet) is proposed to map the dif-ferent input modalities into an embedding space spanned by the learned deep features. Suitable control commands are generated by the simple combination of learned deep features. These deep features represent the intrinsic structural properties of the insulator and the motion pattern of the drones. Particularly, our method is trained purely in simulation and transferred to a real drone directly. Moreover, accurate visual aiming is guaranteed even in strong disturbance environments. Simulation and experimental results verify the high accurate insulator aiming, anti-disturbance, and sim-to-real transfer capabilities of the proposed method. Video: https://youtu.be/Ptlajzvp46A.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"111 12 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":"115764414","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/icra46639.2022.9812136
Wenda Xu, J. Dolan
In this paper, we present a novel convex optimization approach to address the minimum-time speed planning problem over a fixed path with dynamic obstacle constraints and point-wise speed and acceleration constraints. The contributions of this paper are three-fold. First, we formulate the speed planning as an iterative convex optimization problem based on space discretization. Our formulation allows imposing dynamic obstacle constraints and point-wise speed and acceleration constraints simultaneously. Second, we propose a modified vertical cell decomposition method to handle dynamic obstacles. It divides the freespace into channels, where each channel represents a homotopy of free paths and defines convex constraints for dynamic obstacles. Third, we demonstrate significant improvement over previous work on speed planning for typical driving scenarios such as following, merging, and crossing.
{"title":"Speed Planning in Dynamic Environments over a Fixed Path for Autonomous Vehicles","authors":"Wenda Xu, J. Dolan","doi":"10.1109/icra46639.2022.9812136","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9812136","url":null,"abstract":"In this paper, we present a novel convex optimization approach to address the minimum-time speed planning problem over a fixed path with dynamic obstacle constraints and point-wise speed and acceleration constraints. The contributions of this paper are three-fold. First, we formulate the speed planning as an iterative convex optimization problem based on space discretization. Our formulation allows imposing dynamic obstacle constraints and point-wise speed and acceleration constraints simultaneously. Second, we propose a modified vertical cell decomposition method to handle dynamic obstacles. It divides the freespace into channels, where each channel represents a homotopy of free paths and defines convex constraints for dynamic obstacles. Third, we demonstrate significant improvement over previous work on speed planning for typical driving scenarios such as following, merging, and crossing.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"9 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":"124152382","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/icra46639.2022.9811544
Pin-Jie Huang, Chi-An Lu, Kuan-Wen Chen
In this paper, we aim to apply deep saliency prediction to automatic drone exploration, which should consider not only one single image, but multiple images from different view angles or localizations in order to determine the exploration direction. However, little attention has been paid to such saliency prediction problem over multiple-discontinuous-image and none of existing methods take temporal information into consideration, which may mean that the current predicted saliency map is not consistent with the previous predicted results. For this purpose, we propose a method named Temporally-Aggregating Multiple-Discontinuous-Image Saliency Prediction Network (TA-MSNet). It utilizes a transformer-based attention module to correlate relative saliency information among multiple discontinuous images and, furthermore, applies the ConvLSTM module to capture the temporal information. Experiments show that the proposed TA-MSNet can estimate better and more consistent results than previous works for time series data.
{"title":"Temporally-Aggregating Multiple-Discontinuous-Image Saliency Prediction with Transformer-Based Attention","authors":"Pin-Jie Huang, Chi-An Lu, Kuan-Wen Chen","doi":"10.1109/icra46639.2022.9811544","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9811544","url":null,"abstract":"In this paper, we aim to apply deep saliency prediction to automatic drone exploration, which should consider not only one single image, but multiple images from different view angles or localizations in order to determine the exploration direction. However, little attention has been paid to such saliency prediction problem over multiple-discontinuous-image and none of existing methods take temporal information into consideration, which may mean that the current predicted saliency map is not consistent with the previous predicted results. For this purpose, we propose a method named Temporally-Aggregating Multiple-Discontinuous-Image Saliency Prediction Network (TA-MSNet). It utilizes a transformer-based attention module to correlate relative saliency information among multiple discontinuous images and, furthermore, applies the ConvLSTM module to capture the temporal information. Experiments show that the proposed TA-MSNet can estimate better and more consistent results than previous works for time series data.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"19 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":"124545452","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/icra46639.2022.9812191
Akihiro Maruo, A. Shibata, M. Higashimori
This paper presents a novel manipulation method utilizing dynamic deformation of a flexible body with a structural anisotropy. Employing a spiral flexible body, a dynamic underactuated manipulation using its various vibrational patterns is proposed. First, the orbit of the tip of flexible body for the vibrational input to its root is theoretically derived. Subsequently, for flexible bodies with and without the structural anisotropy, structural stiffness and vibrational orbit of the tip of body are analyzed. Through this analysis, the generation mechanism of the orbit change effect according to the input frequency is revealed. Finally, the proposed method is experimentally validated. After confirming the orbit change effect in a spiral flexible body, this effect is applied to an underactuated nonprehensile manipulation where three-Dof motion of an object is controlled by a single actuator.
{"title":"Dynamic Underactuated Manipulator Using a Flexible Body with a Structural Anisotropy","authors":"Akihiro Maruo, A. Shibata, M. Higashimori","doi":"10.1109/icra46639.2022.9812191","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9812191","url":null,"abstract":"This paper presents a novel manipulation method utilizing dynamic deformation of a flexible body with a structural anisotropy. Employing a spiral flexible body, a dynamic underactuated manipulation using its various vibrational patterns is proposed. First, the orbit of the tip of flexible body for the vibrational input to its root is theoretically derived. Subsequently, for flexible bodies with and without the structural anisotropy, structural stiffness and vibrational orbit of the tip of body are analyzed. Through this analysis, the generation mechanism of the orbit change effect according to the input frequency is revealed. Finally, the proposed method is experimentally validated. After confirming the orbit change effect in a spiral flexible body, this effect is applied to an underactuated nonprehensile manipulation where three-Dof motion of an object is controlled by a single actuator.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"79 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":"114352378","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/icra46639.2022.9812030
Alvika Gautam, T. Whiting, X. Cao, M. Goodrich, J. Crandall
While the design of autonomous robots often emphasizes developing proficient robots, another important attribute of autonomous robot systems is their ability to evaluate their own proficiency and limitations. A robot should be able to assess how well it can perform a task before, during, and after it attempts the task. Thus, we consider the following question: How can we design autonomous robots that know their own limits? Toward this end, this paper presents an approach, called assumption-alignment tracking (AAT), for designing autonomous robots that can effectively evaluate their own limits. In AAT, the robot combines (a) measures of how well its decision-making algorithms align with its environment and hardware systems with (b) its past experiences to assess its ability to succeed at a given task. The effectiveness of AAT in assessing a robot's limits are illustrated in a robot navigation task.
{"title":"A Method for Designing Autonomous Robots that Know Their Limits","authors":"Alvika Gautam, T. Whiting, X. Cao, M. Goodrich, J. Crandall","doi":"10.1109/icra46639.2022.9812030","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9812030","url":null,"abstract":"While the design of autonomous robots often emphasizes developing proficient robots, another important attribute of autonomous robot systems is their ability to evaluate their own proficiency and limitations. A robot should be able to assess how well it can perform a task before, during, and after it attempts the task. Thus, we consider the following question: How can we design autonomous robots that know their own limits? Toward this end, this paper presents an approach, called assumption-alignment tracking (AAT), for designing autonomous robots that can effectively evaluate their own limits. In AAT, the robot combines (a) measures of how well its decision-making algorithms align with its environment and hardware systems with (b) its past experiences to assess its ability to succeed at a given task. The effectiveness of AAT in assessing a robot's limits are illustrated in a robot navigation task.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"1 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":"114425055","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/icra46639.2022.9812300
Safoura Sadegh Pour Aji Bishe, Leah Liebelt, Ying Fang, Z. Lerner
Hip exoskeletons may hold potential to augment walking performance and mobility in individuals with disabilities. The purpose of this study was to design and validate a novel autonomous hip exoskeleton with a user-adaptive control strategy capable of reducing the energy cost of level and incline walking in individuals with and without walking impairment. First, in a small cohort of three unimpaired individuals, we validated the ability of our control strategy to provide hip flexion-extension torque that was proportional to the biological hip moment and reduce the energy cost of level and incline walking (24 ± 5% and 13 ± 5% reductions, respectively). Next, in a clinical feasibility experiment with an individual with significant walking impairment from cerebral palsy, we demonstrated that our untethered device and adaptive control scheme improved hip extension by 14° across the gait cycle, reduced average rectus femoris and semitendinosus muscle activity by 23% and 46%, respectively, and resulted in a 15% improvement in metabolic cost relative to walking without wearing the device.
{"title":"A Low-Profile Hip Exoskeleton for Pathological Gait Assistance: Design and Pilot Testing","authors":"Safoura Sadegh Pour Aji Bishe, Leah Liebelt, Ying Fang, Z. Lerner","doi":"10.1109/icra46639.2022.9812300","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9812300","url":null,"abstract":"Hip exoskeletons may hold potential to augment walking performance and mobility in individuals with disabilities. The purpose of this study was to design and validate a novel autonomous hip exoskeleton with a user-adaptive control strategy capable of reducing the energy cost of level and incline walking in individuals with and without walking impairment. First, in a small cohort of three unimpaired individuals, we validated the ability of our control strategy to provide hip flexion-extension torque that was proportional to the biological hip moment and reduce the energy cost of level and incline walking (24 ± 5% and 13 ± 5% reductions, respectively). Next, in a clinical feasibility experiment with an individual with significant walking impairment from cerebral palsy, we demonstrated that our untethered device and adaptive control scheme improved hip extension by 14° across the gait cycle, reduced average rectus femoris and semitendinosus muscle activity by 23% and 46%, respectively, and resulted in a 15% improvement in metabolic cost relative to walking without wearing the device.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"45 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":"114462228","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/ICRA46639.2022.9811655
R. Li, Carlos Esteves, A. Makadia, Pulkit Agrawal
We present a system for accurately predicting stable orientations for diverse rigid objects. We propose to overcome the critical issue of modelling multimodality in the space of rotations by using a conditional generative model to accurately classify contact surfaces. Our system is capable of operating from noisy and partially-observed pointcloud observations captured by real world depth cameras. Our method substantially outperforms the current state-of-the-art systems on a simulated stacking task requiring highly accurate rotations, and demonstrates strong sim2real zero-shot transfer results across a variety of unseen objects on a real world reorientation task.
{"title":"Stable Object Reorientation using Contact Plane Registration","authors":"R. Li, Carlos Esteves, A. Makadia, Pulkit Agrawal","doi":"10.1109/ICRA46639.2022.9811655","DOIUrl":"https://doi.org/10.1109/ICRA46639.2022.9811655","url":null,"abstract":"We present a system for accurately predicting stable orientations for diverse rigid objects. We propose to overcome the critical issue of modelling multimodality in the space of rotations by using a conditional generative model to accurately classify contact surfaces. Our system is capable of operating from noisy and partially-observed pointcloud observations captured by real world depth cameras. Our method substantially outperforms the current state-of-the-art systems on a simulated stacking task requiring highly accurate rotations, and demonstrates strong sim2real zero-shot transfer results across a variety of unseen objects on a real world reorientation task.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"43 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":"114584276","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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