Polynomial linearization for real-time identification of environment Hunt-Crossley models

Schindeler, Ryan; Hashtrudi-Zaad, Keyvan

doi:10.1109/haptics.2016.7463173

Cited by 7 publications

(6 citation statements)

References 17 publications

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“…In the virtual collaboration system, the information of remote environment such as position of the robot, reaction force, geometry of the environment does not be given in real-time because of the communication delays. Schindeler et al, 2016). Most of the previous methods focused on the interaction modeling between robot and static environment, but there were little studies aiming practical interactions involving interaction with moving objects.…”

Section: Challenges In Virtual Collaborationmentioning

confidence: 99%

Robotic remote control based on human motion via virtual collaboration system: A survey

Jung

Song

2018

JAMDSM

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This paper offers a review of the latest robotic remote control schemes that are based on human motion through the virtual collaboration system. The robotic remote control schemes have been studied and developed to combine the intelligence of humans with the precision and mechanical strength of robots. They have performed an important role in some dangerous environments by replacing humans in many difficult jobs, but the lack of intuitive control interfaces causes decreased efficiency. To address this problem, various approaches have been recently investigated, including human motion-based control, visual feedback systems, tactile or force feedback, and other various haptic systems. This paper describes the tendencies of these efforts and discusses possibilities and limitations in three parts: remote control based on human motion, multimodal feedback schemes for realistic interaction, and virtual collaboration systems.

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Section: Challenges In Virtual Collaborationmentioning

confidence: 99%

Robotic remote control based on human motion via virtual collaboration system: A survey

Jung

Song

2018

JAMDSM

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“…Some other relative researches can be found in the literature. 13,14 Most of the previous works are toward interaction modeling with static objects. However, in a practical environment, some tasks often require interaction with movable objects, such as pushing objects to a target position.…”

Section: Introductionsmentioning

confidence: 99%

Translational objects dynamic modeling and correction for point cloud augmented virtual reality–based teleoperation

Song

Wang

et al. 2018

Advances in Mechanical Engineering

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It is a challenging task for operators to interact with the remote environment without its geometric and dynamic knowledge during teleoperation. In this article, a novel system architecture for implementing the translational object modeling and correction during remote interaction is proposed to reconstruct the haptic interaction and predict the object motion at the local virtual reality-based teleoperation. First, a stress mutation analysis method is proposed for segmenting the translational object motion into static phase, critical phase, and sliding phase. And the static limiting friction is originally estimated in the teleoperation area. Meanwhile, mass-damper-spring model and adapted Karnopp friction model are adopted for dynamic modeling in each phase. Second, a novel adaptive forgetting factor recursive least square method is studied for high-accuracy parameter estimation. With the estimated model parameters, the motion of the translational object is predicted at the master side. Meanwhile, for model consistence between the real and virtual environments, a new correction strategy is used to adaptively update the environment model. According to the experimental results, the translational object can be accurately modeled in real time, and its motion at the master side can be predicted precisely and corrected promptly.

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“…In this model, the constant parameters are set to a = b = 3 2 and c = 1. Different learning methods have been suggested in the literature in order to estimate the parameters of this model [9], [19]. Recently, it is shown in [1] and [2] that setting b = 1 2 in the model leads to more accurate results.…”

Section: Introductionmentioning

confidence: 99%

Model estimation and control of compliant contact normal force

Azad

Ortenzi

Lin

et al. 2016

2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids)

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This paper proposes a method to realize desired contact normal forces between humanoids and their compliant environment. By using contact models, desired contact forces are converted to desired deformations of compliant surfaces. To achieve desired forces, deformations are controlled by controlling the contact point positions. Parameters of contact models are assumed to be known or estimated using the approach described in this paper. The proposed methods for estimating the contact parameters and controlling the contact normal force are implemented on a LWR KUKA IV arm. To verify both methods, experiments are performed with the KUKA arm while its end-effector is in contact with two different soft objects.

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Polynomial linearization for real-time identification of environment Hunt-Crossley models

Cited by 7 publications

References 17 publications

Robotic remote control based on human motion via virtual collaboration system: A survey

Robotic remote control based on human motion via virtual collaboration system: A survey

Translational objects dynamic modeling and correction for point cloud augmented virtual reality–based teleoperation

Model estimation and control of compliant contact normal force

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