Pub Date : 2022-05-23DOI: 10.1109/icra46639.2022.9812164
Antonio López-Díaz, Jesús De La Morena, F. Ramos, Ester Vázquez, A. Vázquez
Connection mechanisms are crucial in reconfigurable robots. In this work, we present a novel approach, based on the self-healing property of a hydrogel synthesized by our group, which allows us to easily attach and detach robotic modules using water as the only trigger element. Our connection mechanism does not need external energy to work and it is reversible and soft, being useful for soft modular robots. Tensile, fatigue and adhesion tests are presented to demonstrate the mechanical performance of our mechanism. Two modular soft robots, manipulator and snake, are featured to show the functionality of our approach.
{"title":"A novel hydrogel-based connection mechanism for soft modular robots","authors":"Antonio López-Díaz, Jesús De La Morena, F. Ramos, Ester Vázquez, A. Vázquez","doi":"10.1109/icra46639.2022.9812164","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9812164","url":null,"abstract":"Connection mechanisms are crucial in reconfigurable robots. In this work, we present a novel approach, based on the self-healing property of a hydrogel synthesized by our group, which allows us to easily attach and detach robotic modules using water as the only trigger element. Our connection mechanism does not need external energy to work and it is reversible and soft, being useful for soft modular robots. Tensile, fatigue and adhesion tests are presented to demonstrate the mechanical performance of our mechanism. Two modular soft robots, manipulator and snake, are featured to show the functionality of our approach.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"6 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":"121837378","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/icra46639.2022.9811596
Boqi Li, N. Ammar, Prashant Tiwari, H. Peng
Ride-sharing has important implications for improving the efficiency of mobility-on-demand systems. However, it remains a challenge due to the complex dynamics between vehicles and requests. This paper presents a decentralized ride-sharing algorithm suitable for shared autonomous vehicles (SAVs) deployment. The ride-sharing problem is formulated as a multi-agent reinforcement learning problem. We explore state representation with the request-vehicle graph to encode shareability and potential coordination information. We use a graph attention network to build a hierarchical structure that unifies ride-sharing assignments with rebalancing and handles real-world scenarios where hundreds of user requests can be associated with vehicles. We show results in both generic grid-world and SUMO simulation with real-world data from the Manhattan area. We empirically demonstrate that our proposed approach can achieve similar performance compared with a state-of-the-art centralized optimization method and higher computation efficiency.
{"title":"Decentralized Ride-sharing of Shared Autonomous Vehicles Using Graph Neural Network-Based Reinforcement Learning","authors":"Boqi Li, N. Ammar, Prashant Tiwari, H. Peng","doi":"10.1109/icra46639.2022.9811596","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9811596","url":null,"abstract":"Ride-sharing has important implications for improving the efficiency of mobility-on-demand systems. However, it remains a challenge due to the complex dynamics between vehicles and requests. This paper presents a decentralized ride-sharing algorithm suitable for shared autonomous vehicles (SAVs) deployment. The ride-sharing problem is formulated as a multi-agent reinforcement learning problem. We explore state representation with the request-vehicle graph to encode shareability and potential coordination information. We use a graph attention network to build a hierarchical structure that unifies ride-sharing assignments with rebalancing and handles real-world scenarios where hundreds of user requests can be associated with vehicles. We show results in both generic grid-world and SUMO simulation with real-world data from the Manhattan area. We empirically demonstrate that our proposed approach can achieve similar performance compared with a state-of-the-art centralized optimization method and higher computation efficiency.","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":"121858622","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/icra46639.2022.9811906
Jie Xu, S. Wang, Xingyu Chen, Jiahao Zhang, Xuguang Lan, Nanning Zheng
Human Motion Prediction (HMP) plays a crucial role in safe Human-Robot-Interaction (HRI). Currently, the majority of HMP algorithms are trained by massive pre-collected data. As the training data only contains a few pre-defined motion patterns, these methods cannot handle the unfamiliar motion patterns. Moreover, the pre-collected data are usually non-interactive, which does not consider the real-time responses of collaborators. As a result, these methods usually perform unsatisfactorily in real HRI scenarios. To solve this problem, in this paper, we propose a novel Continual Learning (CL) approach for probabilistic HMP which makes the robot continually learns during its interaction with collaborators. The proposed approach consists of two steps. First, we leverage a Bayesian Neural Network to model diverse uncertainties of observed human motions for collecting online interactive data safely. Then we take Experience Replay and Knowledge Distillation to elevate the model with new experiences while maintaining the knowledge learned before. We first evaluate our approach on a large-scale benchmark dataset Human3.6m. The experimental results show that our approach achieves a lower prediction error compared with the baselines methods. Moreover, our approach could continually learn new motion patterns without forgetting the learned knowledge. We further conduct real-scene experiments using Kinect DK. The results show that our approach can learn the human kinematic model from scratch, which effectively secures the interaction.
{"title":"A Continuous Learning Approach for Probabilistic Human Motion Prediction","authors":"Jie Xu, S. Wang, Xingyu Chen, Jiahao Zhang, Xuguang Lan, Nanning Zheng","doi":"10.1109/icra46639.2022.9811906","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9811906","url":null,"abstract":"Human Motion Prediction (HMP) plays a crucial role in safe Human-Robot-Interaction (HRI). Currently, the majority of HMP algorithms are trained by massive pre-collected data. As the training data only contains a few pre-defined motion patterns, these methods cannot handle the unfamiliar motion patterns. Moreover, the pre-collected data are usually non-interactive, which does not consider the real-time responses of collaborators. As a result, these methods usually perform unsatisfactorily in real HRI scenarios. To solve this problem, in this paper, we propose a novel Continual Learning (CL) approach for probabilistic HMP which makes the robot continually learns during its interaction with collaborators. The proposed approach consists of two steps. First, we leverage a Bayesian Neural Network to model diverse uncertainties of observed human motions for collecting online interactive data safely. Then we take Experience Replay and Knowledge Distillation to elevate the model with new experiences while maintaining the knowledge learned before. We first evaluate our approach on a large-scale benchmark dataset Human3.6m. The experimental results show that our approach achieves a lower prediction error compared with the baselines methods. Moreover, our approach could continually learn new motion patterns without forgetting the learned knowledge. We further conduct real-scene experiments using Kinect DK. The results show that our approach can learn the human kinematic model from scratch, which effectively secures the interaction.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"15 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":"127651687","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/icra46639.2022.9811747
Yukang Shi, Kaisheng Ma
Scene flow prediction is a challenging task that aims at jointly estimating the 3D structure and 3D motion of dynamic scenes. The previous methods concentrate more on point-wise estimation instead of considering the correspondence between objects as well as lacking the sensation of high-level semantic knowledge. In this paper, we propose a concise yet effective method for scene flow prediction. The key idea is to extend the view of all points for computing point cloud features into object-level, thus simultaneously modeling the relationships of the object-level and point-level via an improved transformer. In addition, we introduce a novel unsupervised loss called segmentation-aware loss, which can model semanticaware details to help predict scene flow more accurately and robustly. Since this loss can be trained without any ground truth, it can be used in both supervised training and self-supervised training. Experiments on both supervised training and self-supervised training demonstrate the effectiveness of our method. On supervised training, 3.8%, 22.58%, 10.90% and 21.82 % accuracy boosts than FLOT [23] can be observed on FT3Ds, KITTIs, FT3Do and KITTIo datasets. On self-supervised scheme, 48.23% and 48.96% accuracy boost than PointPWC-Net [40] can be observed on KITTIo and KITTIs datasets.
{"title":"SAFIT: Segmentation-Aware Scene Flow with Improved Transformer","authors":"Yukang Shi, Kaisheng Ma","doi":"10.1109/icra46639.2022.9811747","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9811747","url":null,"abstract":"Scene flow prediction is a challenging task that aims at jointly estimating the 3D structure and 3D motion of dynamic scenes. The previous methods concentrate more on point-wise estimation instead of considering the correspondence between objects as well as lacking the sensation of high-level semantic knowledge. In this paper, we propose a concise yet effective method for scene flow prediction. The key idea is to extend the view of all points for computing point cloud features into object-level, thus simultaneously modeling the relationships of the object-level and point-level via an improved transformer. In addition, we introduce a novel unsupervised loss called segmentation-aware loss, which can model semanticaware details to help predict scene flow more accurately and robustly. Since this loss can be trained without any ground truth, it can be used in both supervised training and self-supervised training. Experiments on both supervised training and self-supervised training demonstrate the effectiveness of our method. On supervised training, 3.8%, 22.58%, 10.90% and 21.82 % accuracy boosts than FLOT [23] can be observed on FT3Ds, KITTIs, FT3Do and KITTIo datasets. On self-supervised scheme, 48.23% and 48.96% accuracy boost than PointPWC-Net [40] can be observed on KITTIo and KITTIs datasets.","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":"128111380","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/icra46639.2022.9812229
Hong Wang, Yao Li, Bing Li
Beetles can walk smoothly on the meshed surface without slipping or getting stuck in the meshed surface due to its stiffness-variable tarsi and expandable hooks on the tip of tarsi. In this study, we find that beetles bend and open their claws proactively to walk freely. Inspired by the mechanism, we designed a centimeter-scale climbing robot, equipping an artificial claw to open and bend in the same cyclic manner as the natural beetles. The robot can climb freely on the mesh surface of 30° without being stuck at a speed of 26.18 mm/s (0.3 body length per second), and the speed was 37.5 mm/s on the 55-degree rough slop. This is the first demonstration of a centimeter-scale robot that can climb on the mesh surface.
{"title":"A beetle-claw inspired miniature mesh climbing robot","authors":"Hong Wang, Yao Li, Bing Li","doi":"10.1109/icra46639.2022.9812229","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9812229","url":null,"abstract":"Beetles can walk smoothly on the meshed surface without slipping or getting stuck in the meshed surface due to its stiffness-variable tarsi and expandable hooks on the tip of tarsi. In this study, we find that beetles bend and open their claws proactively to walk freely. Inspired by the mechanism, we designed a centimeter-scale climbing robot, equipping an artificial claw to open and bend in the same cyclic manner as the natural beetles. The robot can climb freely on the mesh surface of 30° without being stuck at a speed of 26.18 mm/s (0.3 body length per second), and the speed was 37.5 mm/s on the 55-degree rough slop. This is the first demonstration of a centimeter-scale robot that can climb on the mesh surface.","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":"133318898","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/icra46639.2022.9812080
S. Sachidanandam, S. Honarvar, Y. Diaz-Mercado
Human-Swarm Interaction (HSI) is a fast-growing research area in swarm robotics. One challenging aspect of HSI is facilitating effective handling of the many degrees-of-freedom present in robot swarms by humans. One emergent option is the use of Augmented Reality (AR) systems to encode information. AR based interfaces can help provide human operators with visual cues about the swarm's states and control to facilitate decision-making. In research settings, AR systems can address issues such as limited availability of lab spaces, limited access to robotics resources, and the need for the ability to simulate dynamic environments with which robots and humans can interact. Further, to make swarm robotics more accessible and ubiquitous, HSI systems that support remote interaction would allow humans to interact with robot swarms and multi-robot systems regardless of the geographical distance between humans and swarms. Taking these into consideration, we aim to investigate the effectiveness of AR based interfaces as tools for remote interaction in HSI systems. We developed a simple AR based interface and evaluated its effectiveness against an unaugmented interface, by means of remote human user studies where a human operator would control a team of robots remotely through a video call. Our finding suggests that augmentation can improve control accuracy and reduce collision safety violations when performing navigation tasks. Through experimental surveys, it is shown that operators with varying levels of robotics and technology experience overwhelmingly prefer the augmented interface to facilitate swarm control. These results suggest that AR-based interfaces are effective in improving the control experience in remote HSI.
{"title":"Effectiveness of Augmented Reality for Human Swarm Interactions","authors":"S. Sachidanandam, S. Honarvar, Y. Diaz-Mercado","doi":"10.1109/icra46639.2022.9812080","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9812080","url":null,"abstract":"Human-Swarm Interaction (HSI) is a fast-growing research area in swarm robotics. One challenging aspect of HSI is facilitating effective handling of the many degrees-of-freedom present in robot swarms by humans. One emergent option is the use of Augmented Reality (AR) systems to encode information. AR based interfaces can help provide human operators with visual cues about the swarm's states and control to facilitate decision-making. In research settings, AR systems can address issues such as limited availability of lab spaces, limited access to robotics resources, and the need for the ability to simulate dynamic environments with which robots and humans can interact. Further, to make swarm robotics more accessible and ubiquitous, HSI systems that support remote interaction would allow humans to interact with robot swarms and multi-robot systems regardless of the geographical distance between humans and swarms. Taking these into consideration, we aim to investigate the effectiveness of AR based interfaces as tools for remote interaction in HSI systems. We developed a simple AR based interface and evaluated its effectiveness against an unaugmented interface, by means of remote human user studies where a human operator would control a team of robots remotely through a video call. Our finding suggests that augmentation can improve control accuracy and reduce collision safety violations when performing navigation tasks. Through experimental surveys, it is shown that operators with varying levels of robotics and technology experience overwhelmingly prefer the augmented interface to facilitate swarm control. These results suggest that AR-based interfaces are effective in improving the control experience in remote HSI.","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":"133663119","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/icra46639.2022.9811897
Zisos Mitros, S. Sadati, Sotirios Nousias, L. Cruz, C. Bergeles
Continuum surgical robots can navigate anatomical pathways to reach pathological locations deep inside the human body. Their flexibility, however, generally comes with reduced dexterity at their tip and limited workspace. Building on recent work on eccentric tube robots, this paper proposes a new continuum robot architecture and theoretical framework that combines the flexibility of push/pull actuated snake robots and the dexterity offered by concentric tube robotic end-effectors. We designed and present a prototype system as a proof-of-concept, and developed a tailored quasistatic mechanics-based model that describes the shape and end-effector's pose for this new type robotic architecture. The model can accommodate an arbitrary number of arms placed eccentrically with respect to the backbone's neutral axis. Our experiments show that the error between model and experiment is on average 3.56% of the manipulator's overall length. This is in agreement with state of the art models of single type continuum architecture.
{"title":"Design and Quasistatic Modelling of Hybrid Continuum Multi-Arm Robots","authors":"Zisos Mitros, S. Sadati, Sotirios Nousias, L. Cruz, C. Bergeles","doi":"10.1109/icra46639.2022.9811897","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9811897","url":null,"abstract":"Continuum surgical robots can navigate anatomical pathways to reach pathological locations deep inside the human body. Their flexibility, however, generally comes with reduced dexterity at their tip and limited workspace. Building on recent work on eccentric tube robots, this paper proposes a new continuum robot architecture and theoretical framework that combines the flexibility of push/pull actuated snake robots and the dexterity offered by concentric tube robotic end-effectors. We designed and present a prototype system as a proof-of-concept, and developed a tailored quasistatic mechanics-based model that describes the shape and end-effector's pose for this new type robotic architecture. The model can accommodate an arbitrary number of arms placed eccentrically with respect to the backbone's neutral axis. Our experiments show that the error between model and experiment is on average 3.56% of the manipulator's overall length. This is in agreement with state of the art models of single type continuum architecture.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"201 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":"133922088","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/icra46639.2022.9812123
Manu Srivastava, Jake Ammons, A. B. Peerzada, V. Krovi, P. Rangaraju, I. Walker
We present a novel application of continuum robots acting as concrete hoses to support 3D printing of cementitious materials. An industrial concrete hose was fitted with a cable harness and remotely actuated via tendons. The resulting continuum hose robot exhibited non constant curvature. In order to account for this, a new geometric approach to modeling variable curvature inverse kinematics using Euler curves is introduced herein. The new closed form model does not impose any additional computational cost compared to the constant curvature model and results in a marked improvement in the observed performance. Experiments involving 3D printing with cementitious mortar using a continuum hose robot were also conducted.
{"title":"3D Printing of Concrete with a Continuum Robot Hose Using Variable Curvature Kinematics","authors":"Manu Srivastava, Jake Ammons, A. B. Peerzada, V. Krovi, P. Rangaraju, I. Walker","doi":"10.1109/icra46639.2022.9812123","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9812123","url":null,"abstract":"We present a novel application of continuum robots acting as concrete hoses to support 3D printing of cementitious materials. An industrial concrete hose was fitted with a cable harness and remotely actuated via tendons. The resulting continuum hose robot exhibited non constant curvature. In order to account for this, a new geometric approach to modeling variable curvature inverse kinematics using Euler curves is introduced herein. The new closed form model does not impose any additional computational cost compared to the constant curvature model and results in a marked improvement in the observed performance. Experiments involving 3D printing with cementitious mortar using a continuum hose robot were also conducted.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"3 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":"132244652","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/icra46639.2022.9812275
Mathieu-Joel Gervais, Louis-Philippe Lebel, J. Plante
Collaborative robots need to work closely and safely with users while being fast and strong. Fulfilling both these needs simultaneously presents a significant challenge, if not a roadblock, for conventional geared motor technology. Magnetorheological (MR) actuation is an alternative technology that has the potential to exhibit both safety and speed at the same time in a compact and cost-effective envelope. MR actuation has demonstrated great potential for low-DOF mechatronic devices in close collaboration with humans such as exoskeletons and flight control systems but its potential for high-DOF collaborative robots remains widely unexplored. This paper presents the design and experimental validation of a 6 DOF manipulator prototype actuated by semi-delocalized MR clutches. The manipulator is designed with the objective of matching or exceeding the performance requirements of today's cobots in order to verify the potential of MR actuation for such applications. Experimental results show that the prototype has a mass in motion of 5.3 kg and can move a 4.5 kg payload at 1 m/s in a range of 0.885 m. Force bandwidth is above 50 Hz and backdriving forces less than 10% of the joints maximum torque, assuring excellent dynamic performance. Furthermore, the manipulator prototype is shown to be inherently safe and impact-tolerant. In all, results suggest that semi-delocalized MR actuation is a promising solution for high performance cobots although future work is needed for the MR technology to reach full-maturity in robotics.
{"title":"Design Exploration and Experimental Characterization of a 6 Degrees-of-Freedom Robotic Manipulator Powered by Cable-Driven Semi-Delocalized Magnetorheological Actuators","authors":"Mathieu-Joel Gervais, Louis-Philippe Lebel, J. Plante","doi":"10.1109/icra46639.2022.9812275","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9812275","url":null,"abstract":"Collaborative robots need to work closely and safely with users while being fast and strong. Fulfilling both these needs simultaneously presents a significant challenge, if not a roadblock, for conventional geared motor technology. Magnetorheological (MR) actuation is an alternative technology that has the potential to exhibit both safety and speed at the same time in a compact and cost-effective envelope. MR actuation has demonstrated great potential for low-DOF mechatronic devices in close collaboration with humans such as exoskeletons and flight control systems but its potential for high-DOF collaborative robots remains widely unexplored. This paper presents the design and experimental validation of a 6 DOF manipulator prototype actuated by semi-delocalized MR clutches. The manipulator is designed with the objective of matching or exceeding the performance requirements of today's cobots in order to verify the potential of MR actuation for such applications. Experimental results show that the prototype has a mass in motion of 5.3 kg and can move a 4.5 kg payload at 1 m/s in a range of 0.885 m. Force bandwidth is above 50 Hz and backdriving forces less than 10% of the joints maximum torque, assuring excellent dynamic performance. Furthermore, the manipulator prototype is shown to be inherently safe and impact-tolerant. In all, results suggest that semi-delocalized MR actuation is a promising solution for high performance cobots although future work is needed for the MR technology to reach full-maturity in robotics.","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":"134265499","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/icra46639.2022.9811548
Mihai Dragusanu, G. M. Achilli, M. C. Valigi, D. Prattichizzo, M. Malvezzi, G. Salvietti
In this paper, we present a methodology to design soft-rigid grippers able to perform different manipulation tasks. The main idea is the introduction of wave-shaped hinges whose geometrical parameters can be designed to achieve different three-dimensional impedance characteristics. This allows one to use the same tendon-driven actuation to perform different tasks including grasping objects with different shapes and in-hand manipulation of small objects. We report all design procedures and an experimental evaluation of two different prototypes exploiting two possible tasks, the first one is designed to grasp objects adapting to different shapes and dimensions, the second one performs an in-hand manipulation task consisting in object rotation with respect to an axis perpendicular to hand palm, resembling a “screw” movement. Obtained results confirm the feasibility and potentialities of the proposed methodology, that can be applied to obtain 3D printed monolithic fingers able to move in predefined directions when activated through a tendon-driven system, paving the way toward a new task-specific realization of compliant grippers.
{"title":"The Wavejoints: A Novel Methodology to Design Soft-Rigid Grippers Made by Monolithic 3D Printed Fingers with Adjustable Joint Stiffness","authors":"Mihai Dragusanu, G. M. Achilli, M. C. Valigi, D. Prattichizzo, M. Malvezzi, G. Salvietti","doi":"10.1109/icra46639.2022.9811548","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9811548","url":null,"abstract":"In this paper, we present a methodology to design soft-rigid grippers able to perform different manipulation tasks. The main idea is the introduction of wave-shaped hinges whose geometrical parameters can be designed to achieve different three-dimensional impedance characteristics. This allows one to use the same tendon-driven actuation to perform different tasks including grasping objects with different shapes and in-hand manipulation of small objects. We report all design procedures and an experimental evaluation of two different prototypes exploiting two possible tasks, the first one is designed to grasp objects adapting to different shapes and dimensions, the second one performs an in-hand manipulation task consisting in object rotation with respect to an axis perpendicular to hand palm, resembling a “screw” movement. Obtained results confirm the feasibility and potentialities of the proposed methodology, that can be applied to obtain 3D printed monolithic fingers able to move in predefined directions when activated through a tendon-driven system, paving the way toward a new task-specific realization of compliant grippers.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"47 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":"134483759","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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