Pub Date : 2017-11-01DOI: 10.1109/HUMANOIDS.2017.8246952
N. Bohorquez, Pierre-Brice Wieber
When a biped robot is walking in a crowd, being able to adapt the duration of steps is a key element to avoid collisions. Model Predictive Control (MPC) schemes for biped walking usually assume a fixed step duration since adapting it leads to a nonlinear problem, in general. Nonlinear solvers do not guarantee the satisfaction of nonlinear constraints at every iterate and this can be problematic for the real-time operation of robots. We propose a method to make sure that all iterates satisfy the nonlinear constraints by borrowing concepts from robust control: we make the problem robust to nonlinearities within some bounds. These bounds are linear with respect to the variables of the problem and can be adapted online.
{"title":"Adaptive step duration in biped walking: A robust approach to nonlinear constraints","authors":"N. Bohorquez, Pierre-Brice Wieber","doi":"10.1109/HUMANOIDS.2017.8246952","DOIUrl":"https://doi.org/10.1109/HUMANOIDS.2017.8246952","url":null,"abstract":"When a biped robot is walking in a crowd, being able to adapt the duration of steps is a key element to avoid collisions. Model Predictive Control (MPC) schemes for biped walking usually assume a fixed step duration since adapting it leads to a nonlinear problem, in general. Nonlinear solvers do not guarantee the satisfaction of nonlinear constraints at every iterate and this can be problematic for the real-time operation of robots. We propose a method to make sure that all iterates satisfy the nonlinear constraints by borrowing concepts from robust control: we make the problem robust to nonlinearities within some bounds. These bounds are linear with respect to the variables of the problem and can be adapted online.","PeriodicalId":143992,"journal":{"name":"2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116554486","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 : 2017-11-01DOI: 10.1109/HUMANOIDS.2017.8246898
Z. Luo, Xuechao Chen, Zhangguo Yu, Qiang Huang, Libo Meng, Qingqing Li, Weimin Zhang, Wenjuan Guo, A. Ming
Increased walking stability and energy efficiency are both important factors for enhancement of the performance of a biped robot. However, it is difficult to derive the optimal control law that is required using optimal control theory because of the strong nonlinearity and the strong coupling of the robot dynamics equation. Use of numerical methods is one effective way to design an optimal control law. This paper presents a method for optimization of the trajectory of a biped robot's swinging leg that is based on a Gaussian pseudospectral method. We first establish a Lagrange optimization function to optimize both the torque and speed during the walking process. By giving different weights to the torque and the speed, optimization of the different targets can be realized, and as a result, a reduction in the velocity can also change the amplitude of the joint motion fluctuations. The effectiveness of the proposed method is demonstrated via simulations and Experiments.
{"title":"Trajectory optimization of humanoid robots swinging leg","authors":"Z. Luo, Xuechao Chen, Zhangguo Yu, Qiang Huang, Libo Meng, Qingqing Li, Weimin Zhang, Wenjuan Guo, A. Ming","doi":"10.1109/HUMANOIDS.2017.8246898","DOIUrl":"https://doi.org/10.1109/HUMANOIDS.2017.8246898","url":null,"abstract":"Increased walking stability and energy efficiency are both important factors for enhancement of the performance of a biped robot. However, it is difficult to derive the optimal control law that is required using optimal control theory because of the strong nonlinearity and the strong coupling of the robot dynamics equation. Use of numerical methods is one effective way to design an optimal control law. This paper presents a method for optimization of the trajectory of a biped robot's swinging leg that is based on a Gaussian pseudospectral method. We first establish a Lagrange optimization function to optimize both the torque and speed during the walking process. By giving different weights to the torque and the speed, optimization of the different targets can be realized, and as a result, a reduction in the velocity can also change the amplitude of the joint motion fluctuations. The effectiveness of the proposed method is demonstrated via simulations and Experiments.","PeriodicalId":143992,"journal":{"name":"2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116808263","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 : 2017-11-01DOI: 10.1109/HUMANOIDS.2017.8246895
Elco Heijmink, A. Radulescu, Brahayam Pontón, Victor Barasuol, D. Caldwell, C. Semini
The successful execution of complex modern robotic tasks often relies on the correct tuning of a large number of parameters. In this paper we present a methodology for improving the performance of a trotting gait by learning the gait parameters, impedance profile and the gains of the control architecture. We show results on a set of terrains, for various speeds using a realistic simulation of a hydraulically actuated system. Our method achieves a reduction in the gait's mechanical energy consumption during locomotion of up to 26%. The simulation results are validated in experimental trials on the hardware system.
{"title":"Learning optimal gait parameters and impedance profiles for legged locomotion","authors":"Elco Heijmink, A. Radulescu, Brahayam Pontón, Victor Barasuol, D. Caldwell, C. Semini","doi":"10.1109/HUMANOIDS.2017.8246895","DOIUrl":"https://doi.org/10.1109/HUMANOIDS.2017.8246895","url":null,"abstract":"The successful execution of complex modern robotic tasks often relies on the correct tuning of a large number of parameters. In this paper we present a methodology for improving the performance of a trotting gait by learning the gait parameters, impedance profile and the gains of the control architecture. We show results on a set of terrains, for various speeds using a realistic simulation of a hydraulically actuated system. Our method achieves a reduction in the gait's mechanical energy consumption during locomotion of up to 26%. The simulation results are validated in experimental trials on the hardware system.","PeriodicalId":143992,"journal":{"name":"2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132911594","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 : 2017-11-01DOI: 10.1109/HUMANOIDS.2017.8239548
Erfan Shahriari, Aljaz Kramberger, A. Gams, A. Ude, S. Haddadin
In this paper, we develop a framework to encode demonstrated trajectories as periodic dynamic motion primitives (DMP) for an impedance-controlled robot and their modification to fulfil the task objective, i. e. to adapt based on the force feedback and encoded desired wrench profile via an admittance controller. This behavior by itself can violate stability. Therefore, a passivity analysis for the whole system is presented, and based on input power ports and the demonstrated reference power, a passivity observer (PO) is designed. Subsequently, a DMP phase altering law is introduced according to the passivity criterion in order to adjust the phase based on the passivity criterion. However, since this does not necessarily guarantee passivity, a suitable virtual energy tank is used. Experimental results on a Kuka LWR-4 robot polishing an unknown surface underline the real world applicability the suggested controller.
{"title":"Adapting to contacts: Energy tanks and task energy for passivity-based dynamic movement primitives","authors":"Erfan Shahriari, Aljaz Kramberger, A. Gams, A. Ude, S. Haddadin","doi":"10.1109/HUMANOIDS.2017.8239548","DOIUrl":"https://doi.org/10.1109/HUMANOIDS.2017.8239548","url":null,"abstract":"In this paper, we develop a framework to encode demonstrated trajectories as periodic dynamic motion primitives (DMP) for an impedance-controlled robot and their modification to fulfil the task objective, i. e. to adapt based on the force feedback and encoded desired wrench profile via an admittance controller. This behavior by itself can violate stability. Therefore, a passivity analysis for the whole system is presented, and based on input power ports and the demonstrated reference power, a passivity observer (PO) is designed. Subsequently, a DMP phase altering law is introduced according to the passivity criterion in order to adjust the phase based on the passivity criterion. However, since this does not necessarily guarantee passivity, a suitable virtual energy tank is used. Experimental results on a Kuka LWR-4 robot polishing an unknown surface underline the real world applicability the suggested controller.","PeriodicalId":143992,"journal":{"name":"2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134220093","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 : 2017-11-01DOI: 10.1109/HUMANOIDS.2017.8239553
L. Steffan, Lukas Kaul, T. Asfour
Distinguishing between dynamically stable and unstable body poses during the execution of whole-body motions is of equal importance for humanoid robots and humans assisted by robotic exoskeletons. In this work, we present a study for developing a real-time system for detecting dynamic instability based on a small number of body-mounted inertial measurement units (IMUs). To this end, we systematically evaluate different online capable classifiers, operating on the data of 1 to 6 body mounted sensors, trained on a dataset of 50 disturbed motions with nearly 30,000 motion frames recorded at 100 Hz. In contrast to the majority of related studies, our system does not make use of thresholding certain sensor values but instead uses machine learning techniques to detect characteristics and patterns of features of unstable movements. We show that the right combination of classification method and sensor placement on the human body leads to very good detection results with only 3 sensors.
{"title":"Online stability estimation based on inertial sensor data for human and humanoid fall prevention","authors":"L. Steffan, Lukas Kaul, T. Asfour","doi":"10.1109/HUMANOIDS.2017.8239553","DOIUrl":"https://doi.org/10.1109/HUMANOIDS.2017.8239553","url":null,"abstract":"Distinguishing between dynamically stable and unstable body poses during the execution of whole-body motions is of equal importance for humanoid robots and humans assisted by robotic exoskeletons. In this work, we present a study for developing a real-time system for detecting dynamic instability based on a small number of body-mounted inertial measurement units (IMUs). To this end, we systematically evaluate different online capable classifiers, operating on the data of 1 to 6 body mounted sensors, trained on a dataset of 50 disturbed motions with nearly 30,000 motion frames recorded at 100 Hz. In contrast to the majority of related studies, our system does not make use of thresholding certain sensor values but instead uses machine learning techniques to detect characteristics and patterns of features of unstable movements. We show that the right combination of classification method and sensor placement on the human body leads to very good detection results with only 3 sensors.","PeriodicalId":143992,"journal":{"name":"2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134292384","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 : 2017-11-01DOI: 10.1109/HUMANOIDS.2017.8246881
Akihiko Yamaguchi, C. Atkeson
We explore manipulation strategies that use vision-based tactile sensing. FingerVision is a vision-based tactile sensor that provides rich tactile sensation as well as proximity sensing. Although many other tactile sensing methods are expensive in terms of cost and/or processing, FingerVision is a simple and inexpensive approach. We use a transparent skin for fingers. Tracking markers placed on the skin provides contact force and torque estimates, and processing images obtained by seeing through the transparent skin provides static (pose, shape) and dynamic (slip, deformation) information. FingerVision can sense nearby objects even when there is no contact since it is vision-based. Also the slip detection is independent from contact force, which is effective even when the force is too small to measure, such as with origami objects. The results of experiments demonstrate that several manipulation strategies with FingerVision are effective. For example the robot can grasp and pick up an origami crane without crushing it. Video: https://youtu.be/L-YbxcyRghQ
{"title":"Implementing tactile behaviors using FingerVision","authors":"Akihiko Yamaguchi, C. Atkeson","doi":"10.1109/HUMANOIDS.2017.8246881","DOIUrl":"https://doi.org/10.1109/HUMANOIDS.2017.8246881","url":null,"abstract":"We explore manipulation strategies that use vision-based tactile sensing. FingerVision is a vision-based tactile sensor that provides rich tactile sensation as well as proximity sensing. Although many other tactile sensing methods are expensive in terms of cost and/or processing, FingerVision is a simple and inexpensive approach. We use a transparent skin for fingers. Tracking markers placed on the skin provides contact force and torque estimates, and processing images obtained by seeing through the transparent skin provides static (pose, shape) and dynamic (slip, deformation) information. FingerVision can sense nearby objects even when there is no contact since it is vision-based. Also the slip detection is independent from contact force, which is effective even when the force is too small to measure, such as with origami objects. The results of experiments demonstrate that several manipulation strategies with FingerVision are effective. For example the robot can grasp and pick up an origami crane without crushing it. Video: https://youtu.be/L-YbxcyRghQ","PeriodicalId":143992,"journal":{"name":"2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131822264","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 : 2017-11-01DOI: 10.1109/HUMANOIDS.2017.8246897
U. Scarcia, G. Berselli, G. Palli, C. Melchiorri
In this paper, a novel 3D printed Rotational Joint (RJ) embedding an integrated elastic element is presented. The RJ, produced as a single piece by means of an FDM printer, comprises a traditional pin hinge coupled with a pair of spiral torsion springs, providing the desired compliance for the application at hand. Benefits of the proposed design include monolithic manufacturing and possibility to be successfully employed in robotic articulated devices requiring joint elasticity for their functioning. On the other hand, the sub-optimal RJ behavior, mainly caused by the unavoidable friction between 3D printed mating surfaces, must be accurately taken into account for design purposes. In this context, preliminary reliability tests have been performed showing promising results in terms of lifetime and negligible fatigue effects. Then, a mathematical model of the system is derived, which comprises the spring elasticity along with any frictional effects that may be due to either the pin hinge itself or the tendon transmission (frequently employed in underactuated robotic devices). The model parameters have been empirically evaluated by comparing simulated and experimental data. In addition, the last part of the paper describes how the proposed RJ can be effectively employed for the design of modular, underactuated fingers, providing three degrees of freedom and a single tendon transmission. To this end the model of the joint module proposed in this work will be the starting point for the geometry dimensioning of a finger with a desired free closure motion.
{"title":"Modeling, design, and experimental evaluation of rotational elastic joints for underactuated robotic fingers","authors":"U. Scarcia, G. Berselli, G. Palli, C. Melchiorri","doi":"10.1109/HUMANOIDS.2017.8246897","DOIUrl":"https://doi.org/10.1109/HUMANOIDS.2017.8246897","url":null,"abstract":"In this paper, a novel 3D printed Rotational Joint (RJ) embedding an integrated elastic element is presented. The RJ, produced as a single piece by means of an FDM printer, comprises a traditional pin hinge coupled with a pair of spiral torsion springs, providing the desired compliance for the application at hand. Benefits of the proposed design include monolithic manufacturing and possibility to be successfully employed in robotic articulated devices requiring joint elasticity for their functioning. On the other hand, the sub-optimal RJ behavior, mainly caused by the unavoidable friction between 3D printed mating surfaces, must be accurately taken into account for design purposes. In this context, preliminary reliability tests have been performed showing promising results in terms of lifetime and negligible fatigue effects. Then, a mathematical model of the system is derived, which comprises the spring elasticity along with any frictional effects that may be due to either the pin hinge itself or the tendon transmission (frequently employed in underactuated robotic devices). The model parameters have been empirically evaluated by comparing simulated and experimental data. In addition, the last part of the paper describes how the proposed RJ can be effectively employed for the design of modular, underactuated fingers, providing three degrees of freedom and a single tendon transmission. To this end the model of the joint module proposed in this work will be the starting point for the geometry dimensioning of a finger with a desired free closure motion.","PeriodicalId":143992,"journal":{"name":"2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122586840","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 : 2017-11-01DOI: 10.1109/HUMANOIDS.2017.8239544
T. Petrič, Misel Cevzar, J. Babič
What are the benefits of performing a task with other partners in a physically interactive manipulation task setups? By utilizing a novel human motor learning paradigm, where two individuals are aware of each other and their hands are physically connected through an object, we investigated how each partner adapts his/her motor behavior. We first analyzed performance of twenty subjects on a task where a long object, i.e. a pipe, needs to be manipulated into a groove with different tolerances. We tested efficiency and accuracy of performing the task in two different scenarios: a) one human alone — twenty subjects; b) two humans cooperating — ten pairs. We observed that the task performance during cooperative manipulation of an object does not follow any rules, i.e. either both partners get worse, or both get better, or one partner get and one get worse. By exploiting this properties, we propose a novel control algorithm for robots in physically interactive and cooperative human-robot setups, where the robot adapts to the performance of his/hers partner. This way, it allows the human partner to improve his/hers task performance. The results show that the proposed approach can successfully adapt and match motion of the human partner, and thereby enable the human partner to improve his/her motor skills. After adaption, the human coupled with a robotic partner, can perform the task faster.
{"title":"Utilizing speed-accuracy trade-off models for human-robot coadaptation during cooperative groove fitting task","authors":"T. Petrič, Misel Cevzar, J. Babič","doi":"10.1109/HUMANOIDS.2017.8239544","DOIUrl":"https://doi.org/10.1109/HUMANOIDS.2017.8239544","url":null,"abstract":"What are the benefits of performing a task with other partners in a physically interactive manipulation task setups? By utilizing a novel human motor learning paradigm, where two individuals are aware of each other and their hands are physically connected through an object, we investigated how each partner adapts his/her motor behavior. We first analyzed performance of twenty subjects on a task where a long object, i.e. a pipe, needs to be manipulated into a groove with different tolerances. We tested efficiency and accuracy of performing the task in two different scenarios: a) one human alone — twenty subjects; b) two humans cooperating — ten pairs. We observed that the task performance during cooperative manipulation of an object does not follow any rules, i.e. either both partners get worse, or both get better, or one partner get and one get worse. By exploiting this properties, we propose a novel control algorithm for robots in physically interactive and cooperative human-robot setups, where the robot adapts to the performance of his/hers partner. This way, it allows the human partner to improve his/hers task performance. The results show that the proposed approach can successfully adapt and match motion of the human partner, and thereby enable the human partner to improve his/her motor skills. After adaption, the human coupled with a robotic partner, can perform the task faster.","PeriodicalId":143992,"journal":{"name":"2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121281271","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 : 2017-11-01DOI: 10.1109/HUMANOIDS.2017.8246913
Manuel Baum, Matthew Bernstein, Roberto Martín-Martín, S. Höfer, Johannes Kulick, M. Toussaint, A. Kacelnik, O. Brock
How can we close the gap between animals and robots when it comes to intelligently interacting with the environment? On our quest for answers, we have investigated the problem of physically exploring complex mechanical puzzles, called lockboxes. Biologists have discovered that cockatoos are intrinsically motivated to explore and solve such problems through physical explorative behavior. In this work, we study how different strategies shape the robots' exploration, given basic perception-action skills. Our evaluation highlights the influence of different statistical priors on the performance of the exploration strategies, showing that not only a range of computational methods, but also a range of priors could explain different exploration behaviors. We carry out our study of exploration strategies both in simulation and on two robot platforms. This first step towards a fully integrated real-world system allowed us to identify and remove limitations of our prior theoretical work on cross-entropy-based exploration when applied to complex realistic scenarios. In this paper we propose novel variants of this strategy and our experiments verify that the cross-entropy method performs well on a physical lockbox analogue of the cockatoo apparatus, and can generalize to lockboxes of different properties.
{"title":"Opening a lockbox through physical exploration","authors":"Manuel Baum, Matthew Bernstein, Roberto Martín-Martín, S. Höfer, Johannes Kulick, M. Toussaint, A. Kacelnik, O. Brock","doi":"10.1109/HUMANOIDS.2017.8246913","DOIUrl":"https://doi.org/10.1109/HUMANOIDS.2017.8246913","url":null,"abstract":"How can we close the gap between animals and robots when it comes to intelligently interacting with the environment? On our quest for answers, we have investigated the problem of physically exploring complex mechanical puzzles, called lockboxes. Biologists have discovered that cockatoos are intrinsically motivated to explore and solve such problems through physical explorative behavior. In this work, we study how different strategies shape the robots' exploration, given basic perception-action skills. Our evaluation highlights the influence of different statistical priors on the performance of the exploration strategies, showing that not only a range of computational methods, but also a range of priors could explain different exploration behaviors. We carry out our study of exploration strategies both in simulation and on two robot platforms. This first step towards a fully integrated real-world system allowed us to identify and remove limitations of our prior theoretical work on cross-entropy-based exploration when applied to complex realistic scenarios. In this paper we propose novel variants of this strategy and our experiments verify that the cross-entropy method performs well on a physical lockbox analogue of the cockatoo apparatus, and can generalize to lockboxes of different properties.","PeriodicalId":143992,"journal":{"name":"2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114928795","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 : 2017-11-01DOI: 10.1109/HUMANOIDS.2017.8246955
Felix Sygulla, Robert Wittmann, Philipp Seiwald, Arne-Christoph Hildebrandt, Daniel Wahrmann, D. Rixen
Traversing uneven terrain with unexpected changes in ground height still poses a major challenge to walking stabilization of humanoid robots. A common approach to balance a biped in such situations is the control of the ground reaction forces at the feet. However, the dynamics of the center of mass is not considered in existing solutions for this direct force control scheme. In this work, we present a force control method to realize contact forces by accelerating the center of mass, which is directly integrated into our hybrid position/force control scheme. For this, we first introduce an analytical formulation for a contact model in task-space. We evaluate the performance of our approach in simulation and real-world experiments with our humanoid robot LOLA. The integration of center of mass dynamics shows great reduction of upper-body inclination angles for a late contact experiment with 5.5 cm change in ground height. We found that by using the system's center of mass dynamics in the force controller, undesired movements along the under-actuated degrees of freedom can be compensated effectively. We consider our approach a starting point for the development of more sophisticated direct force control concepts for humanoid robots.
{"title":"Hybrid position/force control for biped robot stabilization with integrated center of mass dynamics","authors":"Felix Sygulla, Robert Wittmann, Philipp Seiwald, Arne-Christoph Hildebrandt, Daniel Wahrmann, D. Rixen","doi":"10.1109/HUMANOIDS.2017.8246955","DOIUrl":"https://doi.org/10.1109/HUMANOIDS.2017.8246955","url":null,"abstract":"Traversing uneven terrain with unexpected changes in ground height still poses a major challenge to walking stabilization of humanoid robots. A common approach to balance a biped in such situations is the control of the ground reaction forces at the feet. However, the dynamics of the center of mass is not considered in existing solutions for this direct force control scheme. In this work, we present a force control method to realize contact forces by accelerating the center of mass, which is directly integrated into our hybrid position/force control scheme. For this, we first introduce an analytical formulation for a contact model in task-space. We evaluate the performance of our approach in simulation and real-world experiments with our humanoid robot LOLA. The integration of center of mass dynamics shows great reduction of upper-body inclination angles for a late contact experiment with 5.5 cm change in ground height. We found that by using the system's center of mass dynamics in the force controller, undesired movements along the under-actuated degrees of freedom can be compensated effectively. We consider our approach a starting point for the development of more sophisticated direct force control concepts for humanoid robots.","PeriodicalId":143992,"journal":{"name":"2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127425561","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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