Silvio Traversaro | Istituto Italiano di Tecnologia / Italian Institute of Technology (original) (raw)
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Papers by Silvio Traversaro
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015
2016 IEEE International Conference on Robotics and Automation (ICRA), 2016
This paper presents a novel approach for incremental semiparametric inverse dynamics learning. In... more This paper presents a novel approach for incremental semiparametric inverse dynamics learning. In particular, we consider the mixture of two approaches: Parametric modeling based on rigid body dynamics equations and nonparametric modeling based on incremental kernel methods, with no prior information on the mechanical properties of the system. This yields to an incremental semiparametric approach, leveraging the advantages of both the parametric and nonparametric models. We validate the proposed technique learning the dynamics of one arm of the iCub humanoid robot. * Corresponding author.
Sensors (Basel, Switzerland), 2016
Human motion tracking is a powerful tool used in a large range of applications that require human... more Human motion tracking is a powerful tool used in a large range of applications that require human movement analysis. Although it is a well-established technique, its main limitation is the lack of estimation of real-time kinetics information such as forces and torques during the motion capture. In this paper, we present a novel approach for a human soft wearable force tracking for the simultaneous estimation of whole-body forces along with the motion. The early stage of our framework encompasses traditional passive marker based methods, inertial and contact force sensor modalities and harnesses a probabilistic computational technique for estimating dynamic quantities, originally proposed in the domain of humanoid robot control. We present experimental analysis on subjects performing a two degrees-of-freedom bowing task, and we estimate the motion and kinetics quantities. The results demonstrate the validity of the proposed method. We discuss the possible use of this technique in the...
Lecture Notes in Computer Science, 2015
This paper overviews the whole-body force control framework implemented on the iCub humanoid plat... more This paper overviews the whole-body force control framework implemented on the iCub humanoid platform. This framework consists in a hierarchy of two tasks, where the highest priority task is a force control task, and the lowest one a postural task. The force task achieves the stabilization of a desired centroidal dynamics, i.e., a desired linear and angular momentum of the multi body system. These forces are generated by the internal joint torques, which are related to forces through the rigid constraint equations and the free-floating dynamics. Validation of the framework has been conducted on a real scenario involving the iCub robot balancing on one foot while safely interacting with people.
This paper overviews the whole-body force control framework implemented on the iCub humanoid robo... more This paper overviews the whole-body force control framework implemented on the iCub humanoid robot. This framework consists in a hierarchy of two tasks, where the highest priority task is a force control task, and the lowest one a postural task. Forces are regulated to stabilize a desired cen-troidal dynamics, i.e., a desired linear and angular momentum of the rigid body system. In turn, these forces are generated by the internal links' torques, which are related to forces through the rigid constraint equations and the free-floating dynamics. Validation of the framework has been conducted on a real scenario involving the iCub robot balancing while subject to additional external forces.
2015 IEEE International Conference on Robotics and Automation (ICRA), 2015
Lecture Notes in Computer Science, 2014
Frontiers in Robotics and AI, 2015
This paper details the implementation of state-of-the-art whole-body control algorithms on the hu... more This paper details the implementation of state-of-the-art whole-body control algorithms on the humanoid robot iCub. We regulate the forces between the robot and its surrounding environment to stabilize a desired posture. We assume that the forces and torques are exerted on rigid contacts. The validity of this assumption is guaranteed by constraining the contact forces and torques, e.g., the contact forces must belong to the associated friction cones. The implementation of this control strategy requires the estimation of both joint torques and external forces acting on the robot. We then detail algorithms to obtain these estimates when using a robot with an iCub-like sensor set, i.e., distributed six-axis force-torque sensors and whole-body tactile sensors. A general theory for identifying the robot inertial parameters is also presented. From an actuation standpoint, we show how to implement a joint-torque control in the case of DC brushless motors. In addition, the coupling mechanism of the iCub torso is investigated. The soundness of the entire control architecture is validated in a real scenario involving the robot iCub balancing and making contact with both arms.
This paper proposes techniques to calibrate six-axis force-torque sensors that can be performed i... more This paper proposes techniques to calibrate six-axis force-torque sensors that can be performed in situ, i.e., without removing the sensor from the hosting system. We assume that the force-torque sensor is attached to a rigid body equipped with an accelerometer. Then, the proposed calibration technique uses the measurements of the accelerometer, but requires neither the knowledge of the inertial parameters nor the orientation of the rigid body. The proposed method exploits the geometry induced by the model between the raw measurements of the sensor and the corresponding force-torque. The validation of the approach is performed by calibrating two six-axis force-torque sensors of the iCub humanoid robot.
Identification of inertial parameters is fundamental for the implementation of torque-based contr... more Identification of inertial parameters is fundamental for the implementation of torque-based control in humanoids. At the same time, good models of friction and actuator dynamics are critical for the low-level control of joint torques. We propose a novel method to identify inertial, friction and motor parameters in a single procedure. The identification exploits the measurements of the PWM of the DC motors and a 6-axis force/torque sensor mounted inside the kinematic chain. The partial least-square (PLS) method is used to perform the regression. We identified the inertial, friction and motor parameters of the right arm of the iCub humanoid robot. We verified that the identified model can accurately predict the force/torque sensor measurements and the motor voltages. Moreover, we compared the identified parameters against the CAD parameters, in the prediction of the force/torque sensor measurements. Finally, we showed that the estimated model can effectively detect external contacts, comparing it against a tactile-based contact detection. The presented approach offers some advantages with respect to other state-of-the-art methods, because of its completeness (i.e. it identifies inertial, friction and motor parameters) and simplicity (only one data collection, with no particular requirements).
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015
2016 IEEE International Conference on Robotics and Automation (ICRA), 2016
This paper presents a novel approach for incremental semiparametric inverse dynamics learning. In... more This paper presents a novel approach for incremental semiparametric inverse dynamics learning. In particular, we consider the mixture of two approaches: Parametric modeling based on rigid body dynamics equations and nonparametric modeling based on incremental kernel methods, with no prior information on the mechanical properties of the system. This yields to an incremental semiparametric approach, leveraging the advantages of both the parametric and nonparametric models. We validate the proposed technique learning the dynamics of one arm of the iCub humanoid robot. * Corresponding author.
Sensors (Basel, Switzerland), 2016
Human motion tracking is a powerful tool used in a large range of applications that require human... more Human motion tracking is a powerful tool used in a large range of applications that require human movement analysis. Although it is a well-established technique, its main limitation is the lack of estimation of real-time kinetics information such as forces and torques during the motion capture. In this paper, we present a novel approach for a human soft wearable force tracking for the simultaneous estimation of whole-body forces along with the motion. The early stage of our framework encompasses traditional passive marker based methods, inertial and contact force sensor modalities and harnesses a probabilistic computational technique for estimating dynamic quantities, originally proposed in the domain of humanoid robot control. We present experimental analysis on subjects performing a two degrees-of-freedom bowing task, and we estimate the motion and kinetics quantities. The results demonstrate the validity of the proposed method. We discuss the possible use of this technique in the...
Lecture Notes in Computer Science, 2015
This paper overviews the whole-body force control framework implemented on the iCub humanoid plat... more This paper overviews the whole-body force control framework implemented on the iCub humanoid platform. This framework consists in a hierarchy of two tasks, where the highest priority task is a force control task, and the lowest one a postural task. The force task achieves the stabilization of a desired centroidal dynamics, i.e., a desired linear and angular momentum of the multi body system. These forces are generated by the internal joint torques, which are related to forces through the rigid constraint equations and the free-floating dynamics. Validation of the framework has been conducted on a real scenario involving the iCub robot balancing on one foot while safely interacting with people.
This paper overviews the whole-body force control framework implemented on the iCub humanoid robo... more This paper overviews the whole-body force control framework implemented on the iCub humanoid robot. This framework consists in a hierarchy of two tasks, where the highest priority task is a force control task, and the lowest one a postural task. Forces are regulated to stabilize a desired cen-troidal dynamics, i.e., a desired linear and angular momentum of the rigid body system. In turn, these forces are generated by the internal links' torques, which are related to forces through the rigid constraint equations and the free-floating dynamics. Validation of the framework has been conducted on a real scenario involving the iCub robot balancing while subject to additional external forces.
2015 IEEE International Conference on Robotics and Automation (ICRA), 2015
Lecture Notes in Computer Science, 2014
Frontiers in Robotics and AI, 2015
This paper details the implementation of state-of-the-art whole-body control algorithms on the hu... more This paper details the implementation of state-of-the-art whole-body control algorithms on the humanoid robot iCub. We regulate the forces between the robot and its surrounding environment to stabilize a desired posture. We assume that the forces and torques are exerted on rigid contacts. The validity of this assumption is guaranteed by constraining the contact forces and torques, e.g., the contact forces must belong to the associated friction cones. The implementation of this control strategy requires the estimation of both joint torques and external forces acting on the robot. We then detail algorithms to obtain these estimates when using a robot with an iCub-like sensor set, i.e., distributed six-axis force-torque sensors and whole-body tactile sensors. A general theory for identifying the robot inertial parameters is also presented. From an actuation standpoint, we show how to implement a joint-torque control in the case of DC brushless motors. In addition, the coupling mechanism of the iCub torso is investigated. The soundness of the entire control architecture is validated in a real scenario involving the robot iCub balancing and making contact with both arms.
This paper proposes techniques to calibrate six-axis force-torque sensors that can be performed i... more This paper proposes techniques to calibrate six-axis force-torque sensors that can be performed in situ, i.e., without removing the sensor from the hosting system. We assume that the force-torque sensor is attached to a rigid body equipped with an accelerometer. Then, the proposed calibration technique uses the measurements of the accelerometer, but requires neither the knowledge of the inertial parameters nor the orientation of the rigid body. The proposed method exploits the geometry induced by the model between the raw measurements of the sensor and the corresponding force-torque. The validation of the approach is performed by calibrating two six-axis force-torque sensors of the iCub humanoid robot.
Identification of inertial parameters is fundamental for the implementation of torque-based contr... more Identification of inertial parameters is fundamental for the implementation of torque-based control in humanoids. At the same time, good models of friction and actuator dynamics are critical for the low-level control of joint torques. We propose a novel method to identify inertial, friction and motor parameters in a single procedure. The identification exploits the measurements of the PWM of the DC motors and a 6-axis force/torque sensor mounted inside the kinematic chain. The partial least-square (PLS) method is used to perform the regression. We identified the inertial, friction and motor parameters of the right arm of the iCub humanoid robot. We verified that the identified model can accurately predict the force/torque sensor measurements and the motor voltages. Moreover, we compared the identified parameters against the CAD parameters, in the prediction of the force/torque sensor measurements. Finally, we showed that the estimated model can effectively detect external contacts, comparing it against a tactile-based contact detection. The presented approach offers some advantages with respect to other state-of-the-art methods, because of its completeness (i.e. it identifies inertial, friction and motor parameters) and simplicity (only one data collection, with no particular requirements).