Pub Date : 2019-10-01DOI: 10.1109/Humanoids43949.2019.9035038
Rafael Cisneros, M. Benallegue, M. Morisawa, F. Kanehiro
Humanoid robots rely on precise interaction force to locomote and perform various tasks. Controlling torque usually allows humanoid robots to produce these desired forces on known environments. However, the tracking may be imperfect in the absence of torque feedback or with an imprecise environment model. Furthermore, the presence of geometric errors, regarding the model of the environment, can also lead to discrepancies between desired and actual forces. In this paper, we extend our previous QP-based robust torque control framework to allow force control without requiring joint torque feedback. The control relies only on force/torque sensors at the end effectors, joint encoders and IMUs for kinematic feedback. Additionally, it is formulated to keep consistency with the internal state of the QP solver. We show that hybrid or parallel control, where position and force can be controlled independently, is possible with this approach. The framework is validated with stabilizer-free locomotion on uneven terrain and a multi-contact scenario with reference forces.
{"title":"QP-based task-space hybrid / parallel control for multi-contact motion in a torque-controlled humanoid robot","authors":"Rafael Cisneros, M. Benallegue, M. Morisawa, F. Kanehiro","doi":"10.1109/Humanoids43949.2019.9035038","DOIUrl":"https://doi.org/10.1109/Humanoids43949.2019.9035038","url":null,"abstract":"Humanoid robots rely on precise interaction force to locomote and perform various tasks. Controlling torque usually allows humanoid robots to produce these desired forces on known environments. However, the tracking may be imperfect in the absence of torque feedback or with an imprecise environment model. Furthermore, the presence of geometric errors, regarding the model of the environment, can also lead to discrepancies between desired and actual forces. In this paper, we extend our previous QP-based robust torque control framework to allow force control without requiring joint torque feedback. The control relies only on force/torque sensors at the end effectors, joint encoders and IMUs for kinematic feedback. Additionally, it is formulated to keep consistency with the internal state of the QP solver. We show that hybrid or parallel control, where position and force can be controlled independently, is possible with this approach. The framework is validated with stabilizer-free locomotion on uneven terrain and a multi-contact scenario with reference forces.","PeriodicalId":404758,"journal":{"name":"2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123994359","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 : 2019-10-01DOI: 10.1109/Humanoids43949.2019.9035004
Kevin Stein, K. Mombaur
In this study we analyze slackline balancing, a task where the subject has to maintain balance on a narrow elastic ribbon that is mounted between two anchor points. We investigate a list of potential performance indicators for stability and their relationship to successful and unsuccessful slackline balancing. We captured the motions of 11 subjects of three different skill levels (beginners, sportive beginners and experts) and recorded a total of 205 standing and 180 walking motions on the slackline. We analyzed all trials fitting subject specific, dynamic rigid body models to the measured kinematic motions. The results show that experts are able to precisely control their angular momentum. They mainly balance in the transverse plane and reduce motion in the sagittal plane and around the vertical axis. We also found their walking style being adapted to these criteria. Further, experts are able to move their contact foot in the transverse plane while keeping their center of mass steady. They adjust their ankle and knee compliance in the stance leg. Sufficient center of mass acceleration control in the vertical direction was found to be a necessary skill to walk on a slackline. Additionally, we found consistent hand coordination patterns in all experts and already in sportive beginners.
{"title":"Performance indicators for stability of slackline balancing","authors":"Kevin Stein, K. Mombaur","doi":"10.1109/Humanoids43949.2019.9035004","DOIUrl":"https://doi.org/10.1109/Humanoids43949.2019.9035004","url":null,"abstract":"In this study we analyze slackline balancing, a task where the subject has to maintain balance on a narrow elastic ribbon that is mounted between two anchor points. We investigate a list of potential performance indicators for stability and their relationship to successful and unsuccessful slackline balancing. We captured the motions of 11 subjects of three different skill levels (beginners, sportive beginners and experts) and recorded a total of 205 standing and 180 walking motions on the slackline. We analyzed all trials fitting subject specific, dynamic rigid body models to the measured kinematic motions. The results show that experts are able to precisely control their angular momentum. They mainly balance in the transverse plane and reduce motion in the sagittal plane and around the vertical axis. We also found their walking style being adapted to these criteria. Further, experts are able to move their contact foot in the transverse plane while keeping their center of mass steady. They adjust their ankle and knee compliance in the stance leg. Sufficient center of mass acceleration control in the vertical direction was found to be a necessary skill to walk on a slackline. Additionally, we found consistent hand coordination patterns in all experts and already in sportive beginners.","PeriodicalId":404758,"journal":{"name":"2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids)","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117303253","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 : 2019-10-01DOI: 10.1109/Humanoids43949.2019.9035050
Shuji Oishi, M. Yokozuka, A. Banno
To infer a 3D entire shape from its partial observation, a non-rigid registration algorithm that employs embedded deformations is proposed. We construct a deformation graph on a reference model to discretize the space, and compute a complex deformation as a collection of affine transformations to align the reference model toward the given geometric data. To avoid distortion artifacts during the non-rigid registration, we introduce constraint “As symmetric as possible (ASAP)” on the graph via a generalized cylinder decomposition. ASAP allows model deformation maintaining its underlying local symmetry, which leads to plausible shape completion in the area with no observation. We performed experiments with synthesized data, and demonstrated that the proposed method successfully restored missing surfaces compared with conventional completion techniques.
{"title":"As Symmetric As Possible: Shape Completion with Non-Rigid Registration Leveraging Generalized Cylinder Decomposition","authors":"Shuji Oishi, M. Yokozuka, A. Banno","doi":"10.1109/Humanoids43949.2019.9035050","DOIUrl":"https://doi.org/10.1109/Humanoids43949.2019.9035050","url":null,"abstract":"To infer a 3D entire shape from its partial observation, a non-rigid registration algorithm that employs embedded deformations is proposed. We construct a deformation graph on a reference model to discretize the space, and compute a complex deformation as a collection of affine transformations to align the reference model toward the given geometric data. To avoid distortion artifacts during the non-rigid registration, we introduce constraint “As symmetric as possible (ASAP)” on the graph via a generalized cylinder decomposition. ASAP allows model deformation maintaining its underlying local symmetry, which leads to plausible shape completion in the area with no observation. We performed experiments with synthesized data, and demonstrated that the proposed method successfully restored missing surfaces compared with conventional completion techniques.","PeriodicalId":404758,"journal":{"name":"2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids)","volume":"199 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123519699","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}
When position-controlled biped robot is blind walking on a uneven terrain at a high speed, huge foot contact impacts will be generated. However, traditional admitance control can't absorb the impact and stabilize the robot due to its slow response and Incompleteness. In this paper, we propose a control strategy including respectively designed swing leg control and support leg control with a new approach of control transition. For Swing leg control, double spring damping model is presented to optimize the admitance controller with faster response and better robustness, and a active foot height controller is also proposed to reduce the impact further. On the other hand, the control transition is accomplished by using a bionic fuzzy control. As a result, the foot contact impact can be reduced and the robot can blind walk fast on uneven terrain. Finally, the validity of the proposed strategy is confirmed by the simulation.
{"title":"A novel hierarchical control strategy for biped robot walking on uneven terrain","authors":"Chencheng Dong, Xuechao Chen, Zhangguo Yu, Zelin Huang, Qingqing Li, Qinqin Zhou, Qiang Huang","doi":"10.1109/Humanoids43949.2019.9035039","DOIUrl":"https://doi.org/10.1109/Humanoids43949.2019.9035039","url":null,"abstract":"When position-controlled biped robot is blind walking on a uneven terrain at a high speed, huge foot contact impacts will be generated. However, traditional admitance control can't absorb the impact and stabilize the robot due to its slow response and Incompleteness. In this paper, we propose a control strategy including respectively designed swing leg control and support leg control with a new approach of control transition. For Swing leg control, double spring damping model is presented to optimize the admitance controller with faster response and better robustness, and a active foot height controller is also proposed to reduce the impact further. On the other hand, the control transition is accomplished by using a bionic fuzzy control. As a result, the foot contact impact can be reduced and the robot can blind walk fast on uneven terrain. Finally, the validity of the proposed strategy is confirmed by the simulation.","PeriodicalId":404758,"journal":{"name":"2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122024381","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 : 2019-10-01DOI: 10.1109/Humanoids43949.2019.9035080
Zijia Li, K. Okada, M. Inaba
Humans are able to infer a novel object's functionality by just observing it, due to the fact that an object's geometrical structure usually implies how it can be used, or what we call “object affordance”. While object affordance allows a human to manipulate novel objects intuitively, a robot needs more spatial hints to achieve the same effect. Therefore, we extend the concept of affordance to robotic manipulation field and introduce a novel state trajectory representation to guide a robot to accomplish manipulation tasks. Compared to traditional affordance representations, our representation can not only tell the affordance's location but also show how to perform this affordance. In addition, we present a system, which can effectively learn the state trajectory representation. The experimental results show that our approach outperforms other approaches on the task of predicting state trajectories on novel objects. Finally, we demonstrate how to apply our system and representation on a real robot to tackle robotic manipulation problems.
{"title":"Affordance Action Learning with State Trajectory Representation for Robotic Manipulation","authors":"Zijia Li, K. Okada, M. Inaba","doi":"10.1109/Humanoids43949.2019.9035080","DOIUrl":"https://doi.org/10.1109/Humanoids43949.2019.9035080","url":null,"abstract":"Humans are able to infer a novel object's functionality by just observing it, due to the fact that an object's geometrical structure usually implies how it can be used, or what we call “object affordance”. While object affordance allows a human to manipulate novel objects intuitively, a robot needs more spatial hints to achieve the same effect. Therefore, we extend the concept of affordance to robotic manipulation field and introduce a novel state trajectory representation to guide a robot to accomplish manipulation tasks. Compared to traditional affordance representations, our representation can not only tell the affordance's location but also show how to perform this affordance. In addition, we present a system, which can effectively learn the state trajectory representation. The experimental results show that our approach outperforms other approaches on the task of predicting state trajectories on novel objects. Finally, we demonstrate how to apply our system and representation on a real robot to tackle robotic manipulation problems.","PeriodicalId":404758,"journal":{"name":"2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126648723","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 : 2019-10-01DOI: 10.1109/Humanoids43949.2019.9035014
Tilman Daab, Isabel Patzer, R. Mikut, T. Asfour
In this paper, we address the problem of finding a minimal multi-modal sensor setup for motion classification in lower limb exoskeleton applications while maintaining the classification performance. We present an approach for a systematic exploration of the feature space and feature space dimensionality reduction for motion recognition using Hidden Markov Models (HMMs). We evaluated our approach using IMU and force sensor data with 10 subjects performing 14 different daily activities. We perform a dimensionality reduction on sensor feature level with single- and multi-subjects and we explore the feature space using fine-grained features such as the force value of a single direction. Additionally, we investigate the influence of physical characteristics on the classification quality. Our results show that a subject specific and general reduction of the sensors is possible while still achieving the same classification performance.
{"title":"Feature Space Exploration for Motion Classification Based on Multi-Modal Sensor Data for Lower Limb Exoskeletons","authors":"Tilman Daab, Isabel Patzer, R. Mikut, T. Asfour","doi":"10.1109/Humanoids43949.2019.9035014","DOIUrl":"https://doi.org/10.1109/Humanoids43949.2019.9035014","url":null,"abstract":"In this paper, we address the problem of finding a minimal multi-modal sensor setup for motion classification in lower limb exoskeleton applications while maintaining the classification performance. We present an approach for a systematic exploration of the feature space and feature space dimensionality reduction for motion recognition using Hidden Markov Models (HMMs). We evaluated our approach using IMU and force sensor data with 10 subjects performing 14 different daily activities. We perform a dimensionality reduction on sensor feature level with single- and multi-subjects and we explore the feature space using fine-grained features such as the force value of a single direction. Additionally, we investigate the influence of physical characteristics on the classification quality. Our results show that a subject specific and general reduction of the sensors is possible while still achieving the same classification performance.","PeriodicalId":404758,"journal":{"name":"2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134045275","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 : 2019-10-01DOI: 10.1109/Humanoids43949.2019.9035008
Yuki Asano, Shinsuke Nakashima, Iori Yanokura, Moritaka Onitsuka, Kento Kawaharazuka, Kei Tsuzuki, Yuya Koga, Yusuke Omura, K. Okada, M. Inaba
In this paper, we proposed and implemented ankle-hip-stepping stabilizer for tendon-driven humanoid as a stabilizer that can be used in humanlike knee-stretched posture. The stabilizer is inspired from ankle-hip-stepping strategy of human balance control. The stabilizer is implemented as the integration of two stabilizer, ankle-hip stabilizer as a joint space controller and stepping stabilizer as a work space controller. We conducted evaluation experiments, and confirmed effectiveness of the stabilizer.
{"title":"Ankle-hip-stepping stabilizer on tendon-driven humanoid Kengoro by integration of muscle-joint-work space controllers for knee-stretched humanoid balance","authors":"Yuki Asano, Shinsuke Nakashima, Iori Yanokura, Moritaka Onitsuka, Kento Kawaharazuka, Kei Tsuzuki, Yuya Koga, Yusuke Omura, K. Okada, M. Inaba","doi":"10.1109/Humanoids43949.2019.9035008","DOIUrl":"https://doi.org/10.1109/Humanoids43949.2019.9035008","url":null,"abstract":"In this paper, we proposed and implemented ankle-hip-stepping stabilizer for tendon-driven humanoid as a stabilizer that can be used in humanlike knee-stretched posture. The stabilizer is inspired from ankle-hip-stepping strategy of human balance control. The stabilizer is implemented as the integration of two stabilizer, ankle-hip stabilizer as a joint space controller and stepping stabilizer as a work space controller. We conducted evaluation experiments, and confirmed effectiveness of the stabilizer.","PeriodicalId":404758,"journal":{"name":"2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129388641","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 : 2019-10-01DOI: 10.1109/Humanoids43949.2019.9035051
Nathan Elangovan, Anany Dwivedi, Lucas Gerez, Che-Ming Chang, Minas Liarokapis
Adaptive, underactuated, and compliant robot hands offer a promising alternative to the fully-actuated, rigid robotic devices that are typically considered for the execution of complex tasks that require significant dexterity. The increasing popularity of adaptive hands is due to their ability to extract stable grasps even under significant object pose or other environmental uncertainties, their lightweight and affordable designs and their intuitiveness and easiness of operation. Regarding possible applications, adaptive hands have been successfully used for the execution of both robust grasping and dexterous, in-hand manipulation tasks. However, the particular class of hands also suffers from certain shortcomings and drawbacks. For example, the use of underactuation leads to a post-contact reconfiguration of the fingers that may affect the force exertion capabilities of the hands during pinch grasping. In this paper, we focus on methods to predict the contact forces exerted by adaptive hands in pinch grasps, using their postcontact reconfiguration profile. The bending profiles of the fingers are recorded using ArUco trackers and IMU sensors that are embedded on the adaptive fingers and which are used to train appropriate regression models. More precisely, we examine the efficiency of the machine learning technique (Random Forests) in predicting the exerted contact forces during the reconfiguration phase of an adaptive finger. The accuracy of the proposed method is experimentally validated for a wide range of conditions, involving different prepositionings of the robot finger with respect to the employed force sensor.
{"title":"Employing IMU and ArUco Marker Based Tracking to Decode the Contact Forces Exerted by Adaptive Hands","authors":"Nathan Elangovan, Anany Dwivedi, Lucas Gerez, Che-Ming Chang, Minas Liarokapis","doi":"10.1109/Humanoids43949.2019.9035051","DOIUrl":"https://doi.org/10.1109/Humanoids43949.2019.9035051","url":null,"abstract":"Adaptive, underactuated, and compliant robot hands offer a promising alternative to the fully-actuated, rigid robotic devices that are typically considered for the execution of complex tasks that require significant dexterity. The increasing popularity of adaptive hands is due to their ability to extract stable grasps even under significant object pose or other environmental uncertainties, their lightweight and affordable designs and their intuitiveness and easiness of operation. Regarding possible applications, adaptive hands have been successfully used for the execution of both robust grasping and dexterous, in-hand manipulation tasks. However, the particular class of hands also suffers from certain shortcomings and drawbacks. For example, the use of underactuation leads to a post-contact reconfiguration of the fingers that may affect the force exertion capabilities of the hands during pinch grasping. In this paper, we focus on methods to predict the contact forces exerted by adaptive hands in pinch grasps, using their postcontact reconfiguration profile. The bending profiles of the fingers are recorded using ArUco trackers and IMU sensors that are embedded on the adaptive fingers and which are used to train appropriate regression models. More precisely, we examine the efficiency of the machine learning technique (Random Forests) in predicting the exerted contact forces during the reconfiguration phase of an adaptive finger. The accuracy of the proposed method is experimentally validated for a wide range of conditions, involving different prepositionings of the robot finger with respect to the employed force sensor.","PeriodicalId":404758,"journal":{"name":"2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116206268","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 : 2019-10-01DOI: 10.1109/Humanoids43949.2019.9035049
Kunio Kojima, Yuta Kojio, T. Ishikawa, Fumihito Sugai, Youhei Kakiuchi, K. Okada, M. Inaba
This paper proposes a design method of robots with high specific stiffness for dynamic jumping motions. In the proposed method, we search for high stiffness mechanical structures in a wide design solution space consisting of joint structural parameters as well as frame shape parameters. Particularly in the case of rotary joints driven by linear actuators, we resolve joint moments into actuator's tensile forces and frame's compressive forces and reduce loads exerted on a frame. Though this effect is already known, our method is novel in terms of utilizing this effect for designing robot structures systematically and for saving robot weights. In addition, we introduce a set of the wrenches which would be exerted on a frame (the Frame Load Region) and evaluate the lightness of several robots' structures by using the Frame Load Region. As a resultant of the proposed method, we developed a new life-size humanoid robot prototype JAXON3-P. Then we demonstrate the high motion performance of JAXON3-P and the effectiveness of the proposed design method through jumping motion experiments.
{"title":"A Robot Design Method for Weight Saving Aimed at Dynamic Motions: Design of Humanoid JAXON3-P and Realization of Jump Motions","authors":"Kunio Kojima, Yuta Kojio, T. Ishikawa, Fumihito Sugai, Youhei Kakiuchi, K. Okada, M. Inaba","doi":"10.1109/Humanoids43949.2019.9035049","DOIUrl":"https://doi.org/10.1109/Humanoids43949.2019.9035049","url":null,"abstract":"This paper proposes a design method of robots with high specific stiffness for dynamic jumping motions. In the proposed method, we search for high stiffness mechanical structures in a wide design solution space consisting of joint structural parameters as well as frame shape parameters. Particularly in the case of rotary joints driven by linear actuators, we resolve joint moments into actuator's tensile forces and frame's compressive forces and reduce loads exerted on a frame. Though this effect is already known, our method is novel in terms of utilizing this effect for designing robot structures systematically and for saving robot weights. In addition, we introduce a set of the wrenches which would be exerted on a frame (the Frame Load Region) and evaluate the lightness of several robots' structures by using the Frame Load Region. As a resultant of the proposed method, we developed a new life-size humanoid robot prototype JAXON3-P. Then we demonstrate the high motion performance of JAXON3-P and the effectiveness of the proposed design method through jumping motion experiments.","PeriodicalId":404758,"journal":{"name":"2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids)","volume":"297 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116318395","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 : 2019-10-01DOI: 10.1109/Humanoids43949.2019.9034995
N. Olivieri, Bernd Henze, F. Braghin, M. Roa
Humanoid robots are being tested in multiple applications in different environments, ranging from household and health care facilities to industrial manufacturing or disaster scenarios. Although the first priority of a humanoid robot in any application is to keep its balance and prevent falling, this possibility can never be entirely ruled out due to an internal failure of the robot or to external perturbations. Furthermore, there is no guarantee that the robot can be actively controlled during the fall, which means that the robot will passively fall in the worst case scenario. In order to ensure the safety of humans sharing the same workspace, of nearby equipment, and of the robot itself, it is required to gain knowledge on the expected impact forces when such passive fall occurs, and to create mechanisms that mitigate the consequences of a passive fall. This paper presents an experimental study of the consequences of passive falling on the robot body, analyzes different alternatives to mitigate the impact, and presents an analytical model of the fall that helps to predict the accelerations produced at the impact. The study is conducted using a mockup based on the DLR humanoid robot TORO.
{"title":"Experimental Evaluation and Modeling of Passive Falls in Humanoid Robots","authors":"N. Olivieri, Bernd Henze, F. Braghin, M. Roa","doi":"10.1109/Humanoids43949.2019.9034995","DOIUrl":"https://doi.org/10.1109/Humanoids43949.2019.9034995","url":null,"abstract":"Humanoid robots are being tested in multiple applications in different environments, ranging from household and health care facilities to industrial manufacturing or disaster scenarios. Although the first priority of a humanoid robot in any application is to keep its balance and prevent falling, this possibility can never be entirely ruled out due to an internal failure of the robot or to external perturbations. Furthermore, there is no guarantee that the robot can be actively controlled during the fall, which means that the robot will passively fall in the worst case scenario. In order to ensure the safety of humans sharing the same workspace, of nearby equipment, and of the robot itself, it is required to gain knowledge on the expected impact forces when such passive fall occurs, and to create mechanisms that mitigate the consequences of a passive fall. This paper presents an experimental study of the consequences of passive falling on the robot body, analyzes different alternatives to mitigate the impact, and presents an analytical model of the fall that helps to predict the accelerations produced at the impact. The study is conducted using a mockup based on the DLR humanoid robot TORO.","PeriodicalId":404758,"journal":{"name":"2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123534927","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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