Pub Date : 2016-11-28DOI: 10.1109/IROS.2016.7759828
Samer Abdelmoeti, R. Carloni
In this paper a robust PID controller for quadrotor unmanned aerial vehicles is proposed that uses the parameter space approach. Stability and robustness analyses are carried out in the controller parameter space to determine a set of stable controller gains that guarantee also robustness against system parameter uncertainties. Additionally, the trade-off between robustness and performance is included in the control gain choice. Experimental results validate the proposed approach, where the robust behavior of a quadrotor is shown for step response and path following.
{"title":"Robust control of UAVs using the parameter space approach","authors":"Samer Abdelmoeti, R. Carloni","doi":"10.1109/IROS.2016.7759828","DOIUrl":"https://doi.org/10.1109/IROS.2016.7759828","url":null,"abstract":"In this paper a robust PID controller for quadrotor unmanned aerial vehicles is proposed that uses the parameter space approach. Stability and robustness analyses are carried out in the controller parameter space to determine a set of stable controller gains that guarantee also robustness against system parameter uncertainties. Additionally, the trade-off between robustness and performance is included in the control gain choice. Experimental results validate the proposed approach, where the robust behavior of a quadrotor is shown for step response and path following.","PeriodicalId":296337,"journal":{"name":"2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126247232","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 : 2016-11-28DOI: 10.1109/IROS.2016.7759462
Tetsuro Miyazaki, K. Sanada
This paper proposes a particular case of a robot body design method which determines a degrees of freedom (DOFs) number and link parameters to maximize a target task performance. The DOFs number is an essential point to be considered in the robot body design problem. In this paper, the target task is to make a long throw, and multi DOFs ball throwing robot is designed. Design parameters are the robot body parameters and its motion pattern, and they are designed to maximize ball flying distance under long throw task conditions. To define the link lengths and the robot DOFs number as design parameters, it is assumed that intermediate links of the robot have identical actuators, and these link parameters are defined as functions of link lengths. These links are chained to construct the whole link system. Because of this assumption, the motion equation, which is utilized in the task conditions, is determined by the given robot DOFs number and link lengths. The proposed method was applied to the ball throwing robot model, and its body parameters and motion pattern were designed in the proposed calculation algorithm. As a result, 5 DOFs robot and its throwing motion were obtained, and the ball flying distance was maximized. The ball flying distance was changed along with the DOFs number, and the effectiveness of the proposed design method was demonstrated.
{"title":"Robot body design including degrees of freedom and link parameters maximizing ball throwing performance","authors":"Tetsuro Miyazaki, K. Sanada","doi":"10.1109/IROS.2016.7759462","DOIUrl":"https://doi.org/10.1109/IROS.2016.7759462","url":null,"abstract":"This paper proposes a particular case of a robot body design method which determines a degrees of freedom (DOFs) number and link parameters to maximize a target task performance. The DOFs number is an essential point to be considered in the robot body design problem. In this paper, the target task is to make a long throw, and multi DOFs ball throwing robot is designed. Design parameters are the robot body parameters and its motion pattern, and they are designed to maximize ball flying distance under long throw task conditions. To define the link lengths and the robot DOFs number as design parameters, it is assumed that intermediate links of the robot have identical actuators, and these link parameters are defined as functions of link lengths. These links are chained to construct the whole link system. Because of this assumption, the motion equation, which is utilized in the task conditions, is determined by the given robot DOFs number and link lengths. The proposed method was applied to the ball throwing robot model, and its body parameters and motion pattern were designed in the proposed calculation algorithm. As a result, 5 DOFs robot and its throwing motion were obtained, and the ball flying distance was maximized. The ball flying distance was changed along with the DOFs number, and the effectiveness of the proposed design method was demonstrated.","PeriodicalId":296337,"journal":{"name":"2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"27 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121015380","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 : 2016-11-28DOI: 10.1109/IROS.2016.7759485
Shan Luo, Wenxuan Mou, K. Althoefer, Hongbin Liu
Tactile data and kinesthetic cues are two important sensing sources in robot object recognition and are complementary to each other. In this paper, we propose a novel algorithm named Iterative Closest Labeled Point (iCLAP) to recognize objects using both tactile and kinesthetic information. The iCLAP first assigns different local tactile features with distinct label numbers. The label numbers of the tactile features together with their associated 3D positions form a 4D point cloud of the object. In this manner, the two sensing modalities are merged to form a synthesized perception of the touched object. To recognize an object, the partial 4D point cloud obtained from a number of touches iteratively matches with all the reference cloud models to identify the best fit. An extensive evaluation study with 20 real objects shows that our proposed iCLAP approach outperforms those using either of the separate sensing modalities, with a substantial recognition rate improvement of up to 18%.
{"title":"Iterative Closest Labeled Point for tactile object shape recognition","authors":"Shan Luo, Wenxuan Mou, K. Althoefer, Hongbin Liu","doi":"10.1109/IROS.2016.7759485","DOIUrl":"https://doi.org/10.1109/IROS.2016.7759485","url":null,"abstract":"Tactile data and kinesthetic cues are two important sensing sources in robot object recognition and are complementary to each other. In this paper, we propose a novel algorithm named Iterative Closest Labeled Point (iCLAP) to recognize objects using both tactile and kinesthetic information. The iCLAP first assigns different local tactile features with distinct label numbers. The label numbers of the tactile features together with their associated 3D positions form a 4D point cloud of the object. In this manner, the two sensing modalities are merged to form a synthesized perception of the touched object. To recognize an object, the partial 4D point cloud obtained from a number of touches iteratively matches with all the reference cloud models to identify the best fit. An extensive evaluation study with 20 real objects shows that our proposed iCLAP approach outperforms those using either of the separate sensing modalities, with a substantial recognition rate improvement of up to 18%.","PeriodicalId":296337,"journal":{"name":"2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129907336","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 : 2016-11-28DOI: 10.1109/IROS.2016.7759571
G. Thomas, L. Sentis
This paper considers the problem of numerically efficient planning for legged robot locomotion, aiming towards reactive multi-contact planning as a reliability feature. We propose to decompose the problem into two parts: an extremely low dimensional kinematic search, which only adjusts a geometric path through space; and a dynamic optimization, which we focus on in this paper. This dynamic optimization also includes the selection of foot steps and hand-holds-in the special case of instantaneous foot re-location. This case is interesting because (1) it is a limiting behavior for algorithms with a foot switching cost, (2) it may have merit as a heuristic to guide search, and (3) it could act as a building block towards algorithms which do consider foot transition cost. The algorithm bears similarity both to phase space locomotion planning techniques for bipedal walking and the minimum time trajectory scaling problem for robot arms. A fundamental aspect of the algorithm's efficiency is its use of linear programming with reuse of the active set of inequality constraints. Simulation results in a simplified setting are used to demonstrate the planning of agile locomotion behaviors.
{"title":"Towards computationally efficient planning of dynamic multi-contact locomotion","authors":"G. Thomas, L. Sentis","doi":"10.1109/IROS.2016.7759571","DOIUrl":"https://doi.org/10.1109/IROS.2016.7759571","url":null,"abstract":"This paper considers the problem of numerically efficient planning for legged robot locomotion, aiming towards reactive multi-contact planning as a reliability feature. We propose to decompose the problem into two parts: an extremely low dimensional kinematic search, which only adjusts a geometric path through space; and a dynamic optimization, which we focus on in this paper. This dynamic optimization also includes the selection of foot steps and hand-holds-in the special case of instantaneous foot re-location. This case is interesting because (1) it is a limiting behavior for algorithms with a foot switching cost, (2) it may have merit as a heuristic to guide search, and (3) it could act as a building block towards algorithms which do consider foot transition cost. The algorithm bears similarity both to phase space locomotion planning techniques for bipedal walking and the minimum time trajectory scaling problem for robot arms. A fundamental aspect of the algorithm's efficiency is its use of linear programming with reuse of the active set of inequality constraints. Simulation results in a simplified setting are used to demonstrate the planning of agile locomotion behaviors.","PeriodicalId":296337,"journal":{"name":"2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128094272","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 : 2016-11-28DOI: 10.1109/IROS.2016.7759127
M. Racca, J. Pajarinen, Alberto Montebelli, V. Kyrki
Learning to perform tasks like pulling a door handle or pushing a button, inherently easy for a human, can be surprisingly difficult for a robot. A crucial problem in these kinds of in-contact tasks is the context specificity of pose and force requirements. In this paper, a robot learns in-contact tasks from human kinesthetic demonstrations. To address the need to balance between the position and force constraints, we propose a model based on the hidden semi-Markov model (HSMM) and Cartesian impedance control. The model captures uncertainty over time and space and allows the robot to smoothly satisfy a task's position and force constraints by online modulation of impedance controller stiffness according to the HSMM state belief. In experiments, a KUKA LWR 4+ robotic arm equipped with a force/torque sensor at the wrist successfully learns from human demonstrations how to pull a door handle and push a button.
{"title":"Learning in-contact control strategies from demonstration","authors":"M. Racca, J. Pajarinen, Alberto Montebelli, V. Kyrki","doi":"10.1109/IROS.2016.7759127","DOIUrl":"https://doi.org/10.1109/IROS.2016.7759127","url":null,"abstract":"Learning to perform tasks like pulling a door handle or pushing a button, inherently easy for a human, can be surprisingly difficult for a robot. A crucial problem in these kinds of in-contact tasks is the context specificity of pose and force requirements. In this paper, a robot learns in-contact tasks from human kinesthetic demonstrations. To address the need to balance between the position and force constraints, we propose a model based on the hidden semi-Markov model (HSMM) and Cartesian impedance control. The model captures uncertainty over time and space and allows the robot to smoothly satisfy a task's position and force constraints by online modulation of impedance controller stiffness according to the HSMM state belief. In experiments, a KUKA LWR 4+ robotic arm equipped with a force/torque sensor at the wrist successfully learns from human demonstrations how to pull a door handle and push a button.","PeriodicalId":296337,"journal":{"name":"2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127574956","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 : 2016-11-28DOI: 10.1109/IROS.2016.7759398
Xiaojian Li, Chichi Liu, Shuxun Chen, Yong Wang, S. Cheng, Dong Sun
As rapid development of precision medicine, in vivo manipulation of micro/nano-scaled particles have attracted increasing attention in recent years. To accommodate complex in-vivo environment, robot-aided automated manipulation technology is highly demanded in trapping and controlling micro/nano-particles stably and effectively. This paper presents an in-vivo cell manipulation system, where a disturbance compensation controller is utilized to minimize the effect of fluid (e.g., blood flow) on the cell. The controller has exhibited advantages in adjusting cell tracking trajectory online, minimizing the steady-state error, and eliminating overshoot. Simulation and experimental results verify the performance of the controller.
{"title":"Automated in-vivo transportation of biological cells with a disturbance compensation controller","authors":"Xiaojian Li, Chichi Liu, Shuxun Chen, Yong Wang, S. Cheng, Dong Sun","doi":"10.1109/IROS.2016.7759398","DOIUrl":"https://doi.org/10.1109/IROS.2016.7759398","url":null,"abstract":"As rapid development of precision medicine, in vivo manipulation of micro/nano-scaled particles have attracted increasing attention in recent years. To accommodate complex in-vivo environment, robot-aided automated manipulation technology is highly demanded in trapping and controlling micro/nano-particles stably and effectively. This paper presents an in-vivo cell manipulation system, where a disturbance compensation controller is utilized to minimize the effect of fluid (e.g., blood flow) on the cell. The controller has exhibited advantages in adjusting cell tracking trajectory online, minimizing the steady-state error, and eliminating overshoot. Simulation and experimental results verify the performance of the controller.","PeriodicalId":296337,"journal":{"name":"2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124896533","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 : 2016-11-28DOI: 10.1109/IROS.2016.7759116
Athanasios S. Polydoros, L. Nalpantidis
Many robot learning algorithms depend on a model of the robot's forward dynamics for simulating potential trajectories and ultimately learning a required task. In this paper, we present a data-driven reservoir computing approach and apply it for learning forward dynamics models. Our proposed machine learning algorithm exploits the concepts of dynamic reservoir, self-organized learning and Bayesian inference. We have evaluated our approach on datasets gathered from two industrial robotic manipulators and compared it on both step-by-step and multi-step trajectory prediction scenarios with state-of-the-art algorithms. The evaluation considers the algorithms' convergence and prediction performance on joint and operational space for varying prediction horizons, as well as computational time. Results show that the proposed algorithm performs better than the state-of-the-art, converges fast and can achieve accurate predictions over longer horizons, which makes it a reliable, data-efficient approach for learning forward models.
{"title":"A reservoir computing approach for learning forward dynamics of industrial manipulators","authors":"Athanasios S. Polydoros, L. Nalpantidis","doi":"10.1109/IROS.2016.7759116","DOIUrl":"https://doi.org/10.1109/IROS.2016.7759116","url":null,"abstract":"Many robot learning algorithms depend on a model of the robot's forward dynamics for simulating potential trajectories and ultimately learning a required task. In this paper, we present a data-driven reservoir computing approach and apply it for learning forward dynamics models. Our proposed machine learning algorithm exploits the concepts of dynamic reservoir, self-organized learning and Bayesian inference. We have evaluated our approach on datasets gathered from two industrial robotic manipulators and compared it on both step-by-step and multi-step trajectory prediction scenarios with state-of-the-art algorithms. The evaluation considers the algorithms' convergence and prediction performance on joint and operational space for varying prediction horizons, as well as computational time. Results show that the proposed algorithm performs better than the state-of-the-art, converges fast and can achieve accurate predictions over longer horizons, which makes it a reliable, data-efficient approach for learning forward models.","PeriodicalId":296337,"journal":{"name":"2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"221 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115081607","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 : 2016-11-28DOI: 10.1109/IROS.2016.7759851
Xiao Sun, K. Hashimoto, Shinya Hamamoto, Ayanori Koizumi, T. Matsuzawa, Tomotaka Teramachi, A. Takanishi
This paper introduces a motion planning method to generate ladder climbing motion for a four-limbed robot. This method contains the following points: (1) independent planning of path and time in 3 dimensional space for trajectory planning; (2) path length minimization according to given midpoints. In trajectory planning, arc-length parameterization is used to separate path planning and time planning so that they can be done independently. After path is planned, time planning along the planned path can be given freely to meet our requirement, such as speed and acceleration adjustment for the protection of motors, optimization for dynamics analysis, dynamic obstacle avoidance and so on. Results from simulations and experiments authenticate the validity of our motion generation method.
{"title":"Trajectory generation for ladder climbing motion with separated path and time planning","authors":"Xiao Sun, K. Hashimoto, Shinya Hamamoto, Ayanori Koizumi, T. Matsuzawa, Tomotaka Teramachi, A. Takanishi","doi":"10.1109/IROS.2016.7759851","DOIUrl":"https://doi.org/10.1109/IROS.2016.7759851","url":null,"abstract":"This paper introduces a motion planning method to generate ladder climbing motion for a four-limbed robot. This method contains the following points: (1) independent planning of path and time in 3 dimensional space for trajectory planning; (2) path length minimization according to given midpoints. In trajectory planning, arc-length parameterization is used to separate path planning and time planning so that they can be done independently. After path is planned, time planning along the planned path can be given freely to meet our requirement, such as speed and acceleration adjustment for the protection of motors, optimization for dynamics analysis, dynamic obstacle avoidance and so on. Results from simulations and experiments authenticate the validity of our motion generation method.","PeriodicalId":296337,"journal":{"name":"2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131580713","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 : 2016-11-28DOI: 10.1109/IROS.2016.7759155
Todor Stoyanov, R. Krug, Rajkumar Muthusamy, V. Kyrki
Grasping systems that build upon meticulously planned hand postures rely on precise knowledge of object geometry, mass and frictional properties - assumptions which are often violated in practice. In this work, we propose an alternative solution to the problem of grasp acquisition in simple autonomous pick and place scenarios, by utilizing the concept of grasp envelopes: sets of constraints on gripper postures. We propose a fast method for extracting grasp envelopes for objects that fit within a known shape category, placed in an unknown environment. Our approach is based on grasp envelope primitives, which encode knowledge of human grasping strategies. We use environment models, reconstructed from noisy sensor observations, to refine the grasp envelope primitives and extract bounded envelopes of collision-free gripper postures. Also, we evaluate the envelope extraction procedure both in a stand alone fashion, as well as an integrated component of an autonomous picking system.
{"title":"Grasp envelopes: Extracting constraints on gripper postures from online reconstructed 3D models","authors":"Todor Stoyanov, R. Krug, Rajkumar Muthusamy, V. Kyrki","doi":"10.1109/IROS.2016.7759155","DOIUrl":"https://doi.org/10.1109/IROS.2016.7759155","url":null,"abstract":"Grasping systems that build upon meticulously planned hand postures rely on precise knowledge of object geometry, mass and frictional properties - assumptions which are often violated in practice. In this work, we propose an alternative solution to the problem of grasp acquisition in simple autonomous pick and place scenarios, by utilizing the concept of grasp envelopes: sets of constraints on gripper postures. We propose a fast method for extracting grasp envelopes for objects that fit within a known shape category, placed in an unknown environment. Our approach is based on grasp envelope primitives, which encode knowledge of human grasping strategies. We use environment models, reconstructed from noisy sensor observations, to refine the grasp envelope primitives and extract bounded envelopes of collision-free gripper postures. Also, we evaluate the envelope extraction procedure both in a stand alone fashion, as well as an integrated component of an autonomous picking system.","PeriodicalId":296337,"journal":{"name":"2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126798445","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 : 2016-11-28DOI: 10.1109/IROS.2016.7759078
Gonzalo Aguirre Dominguez, Mitsuhiro Kamezaki, Shan He, S. Somlor, A. Schmitz, S. Sugano
The advantages of mechanical compliance have driven the development of devices using new smart materials. A new kind of magnetorheological piston based on a toroidal array of magnetorheological valves, has been previously tested to prove its feasibility. However, being an initial prototype its potential was still limited by its complex design, and low output force. This study presents the revisions done to the design with several improvements targeting key performance parameters. An improved annular piston design is also introduced as comparison with conventional devices. The toroidal and annular piston head prototypes are built and tested, and their force performance compared with the previous iteration. The experimental results show an overall performance improvement of the toroidal assembly. However, the force model used in the study still fails to accurately predict the magnetic flux at the gaps of the piston head. This deviation is later verify and corrected using a FEM analysis. The force performance of the new toroidal assembly is on par with the commonplace annular design. It also displays a more linear behaviour, at the expense of lower energy efficiency. Finally, it also shows potential for a greater degree of customisation to meet different system requirements.
{"title":"Design optimisation and performance evaluation of a toroidal magnetorheological hydraulic piston head","authors":"Gonzalo Aguirre Dominguez, Mitsuhiro Kamezaki, Shan He, S. Somlor, A. Schmitz, S. Sugano","doi":"10.1109/IROS.2016.7759078","DOIUrl":"https://doi.org/10.1109/IROS.2016.7759078","url":null,"abstract":"The advantages of mechanical compliance have driven the development of devices using new smart materials. A new kind of magnetorheological piston based on a toroidal array of magnetorheological valves, has been previously tested to prove its feasibility. However, being an initial prototype its potential was still limited by its complex design, and low output force. This study presents the revisions done to the design with several improvements targeting key performance parameters. An improved annular piston design is also introduced as comparison with conventional devices. The toroidal and annular piston head prototypes are built and tested, and their force performance compared with the previous iteration. The experimental results show an overall performance improvement of the toroidal assembly. However, the force model used in the study still fails to accurately predict the magnetic flux at the gaps of the piston head. This deviation is later verify and corrected using a FEM analysis. The force performance of the new toroidal assembly is on par with the commonplace annular design. It also displays a more linear behaviour, at the expense of lower energy efficiency. Finally, it also shows potential for a greater degree of customisation to meet different system requirements.","PeriodicalId":296337,"journal":{"name":"2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123661539","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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