Internal force computation of grasped object using joint torques

Xue, Zhixing; Schmidt, Michael D.; Zoellner, J. Marius; Dillmann, Ruediger

doi:10.1109/sice.2008.4655140

Cited by 3 publications

(1 citation statement)

References 13 publications

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“…The problem of computing the forces exerted on a manipulated object using the torques applied to the joint motors has already been previously addressed, e.g. using a robotic hand without tactile sensors [8], or using a bi-manual robot [9] looking for the optimization of the forces applied on the manipulated object, but graphical representations of the real applied forces to help the user understanding the grasp during the development of grasping and manipulation strategies are not available.…”

Section: Introductionmentioning

confidence: 99%

Graphical visualization of contact forces and hand movements during in-hand manipulation

Suárez

Montano

2022

2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA)

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The paper presents a tool to graphically display the contact forces applied by the fingers of a robotic hand when doing grasping and in-hand manipulation. The forces are computed in two ways, on one side, directly using the measurements of tactile forces in the fingertips and, on the other, using the torques applied by the motors in the finger joints. The implemented tool also allows to command and move the real robotic hand by specifying the complete hand configuration or any single joint, and see graphically the hand simulation. Real results are shown using the Allegro hand with tactile sensors WTS-FT.

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Section: Introductionmentioning

confidence: 99%

Graphical visualization of contact forces and hand movements during in-hand manipulation

Suárez

Montano

2022

2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA)

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Contact force computation for bimanual grasps

Rojas-de-Silva

Suárez

2017

2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)

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This paper presents a method to compute con-\ud tact forces for bimanual grasps. The method is based on the\ud optimization of the force distribution of the hands and min-\ud imizing the force exerted by each finger, using two different\ud cost functions. Both cost functions and the constrains of the\ud optimization problem are formulated as functions of the joint\ud torques based on the existing relation between the grasping\ud forces, the hand-jacobian matrix and the torque of the joint\ud fingers. Additionally, a bimanual grasp index is presented to\ud measure the force distribution between the hands. The paper\ud includes some application examples of the proposed approacPeer ReviewedPostprint (author's final draft

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Monitoring of manipulation activities for a service robot using supervised learning

Ruehl

Xue

Dillmann

2012

2012 IEEE International Conference on Robotics and Automation

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To be a good helper, grasping and manipulation are the most important abilities of a service robot. It should be able to adapt its manipulation actions to new tasks and environments. During the execution, it is important to rate the success of actions, so that the robot can plan and execute further actions to correct and recover from the failed actions.The successful execution of manipulation actions depends on various factors during the whole execution, such as the position of the robotic hand and forces exerted by the robot. The goal of the manipulation action monitoring is to estimate the sucess state from the huge amount of data collected during the execution. The main challenge to solve this problem is to identify the success or failure state from the the high dimensional data collection.We propose a method to classify ongoing activities using a set of support vector machines (SVM). After a supervised training process with manually labeled successful or failure results, our system can correctly estimate the resulting state of a manipulation activity. We present experiments on our bimanual manipulation demonstrator and evaluate the results.

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Internal force computation of grasped object using joint torques

Cited by 3 publications

References 13 publications

Graphical visualization of contact forces and hand movements during in-hand manipulation

Graphical visualization of contact forces and hand movements during in-hand manipulation

Contact force computation for bimanual grasps

Monitoring of manipulation activities for a service robot using supervised learning

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