Human-Oriented Control for Haptic Teleoperation

Hirche, Sandra; Buss, Martin

doi:10.1109/jproc.2011.2175150

Cited by 198 publications

(96 citation statements)

References 88 publications

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“…The damping b must be velocity-dependent to account for generic coulomb friction. It can be derived through experimental identification of the input/output behavior of the real setup [5] as explained in Section 2.2. The decision for the approximation of the physics engine with a mass-damper system is driven by the VE models used in [14,9], which are based on the same model.…”

Section: Shve Modelmentioning

confidence: 99%

“…The decision for the approximation of the physics engine with a mass-damper system is driven by the VE models used in [14,9], which are based on the same model. Second-order linear dynamic systems are generally used to model the remote environment in TPTA systems for transparency analysis [5]. The equation of motion of the cube, following the model in Fig.…”

Section: Shve Modelmentioning

confidence: 99%

“…On the other hand, the centralized physics engine comes with the drawback of local object states at the clients being updated only after a full round-trip time (RTT). As a result, transparency of the SHVE, which is one of the main goals in control design for telepresence and teleaction (TPTA) systems [5], is lost with increasing communication delay [9]. A TPTA system is called transparent if the human can not perceive a difference between direct interaction with an environment and remote interaction through the TPTA system [12].…”

Section: Introductionmentioning

confidence: 99%

“…The human perceives the object as being heavier than expected and the transparency of the SHVE is lost. Transparency, however, can be critical for human decision making, e.g., in haptically enhanced virtual surgical training [5].…”

Section: Introductionmentioning

confidence: 99%

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Delay compensation in Shared Haptic Virtual Environments

Schuwerk

Chaudhari

Steinbach

2014

2014 IEEE Haptics Symposium (HAPTICS)

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Shared Haptic Virtual Environments (SHVEs) are often realized using a client-server architecture. At the server, a physics simulation engine calculates the object states based on the position information received from the clients. At the clients, the object state information, received from the server, is used to update the local copy of the virtual environment. Forces displayed to the user through a haptic device are computed locally at the client based on the interactions with the objects. Communication delay leads to delayed object state updates and increased interaction forces rendered at the clients. Users perceive this as increased object weight. In this paper, we systematically analyze the loss of transparency caused by communication delay and propose a novel adaptive force rendering scheme to compensate for it. The proposed scheme reduces the objects' stiffness at the clients, based on delay, device velocity and motion constraints of the objects, only if necessary to achieve perceptual transparency. Simulations and subjective evaluations show that the effect of increased weight of objects is successfully compensated for the tested delay range of up to 150 ms. At the same time, if the object is unmovable, the perception of interaction with a rigid object is preserved.

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Section: Shve Modelmentioning

confidence: 99%

Section: Shve Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Delay compensation in Shared Haptic Virtual Environments

Schuwerk

Chaudhari

Steinbach

2014

2014 IEEE Haptics Symposium (HAPTICS)

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“…Another way to communicate complex motions to a robot, which is more natural, is to track the operator arm motion which is used to complete the required task using contacting electromagnetic tracking sensors, inertial sensors and gloves instrumented with angle sensors. However, these contacting devices may hinder natural human-limb motions [4]- [6].…”

Section: Introductionmentioning

confidence: 99%

Kinect-Based Humanoid Robotic Manipulator for Human Upper Limbs Movements Tracking

Al-Faiz¹,

Shanta²

2015

ICA

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This paper presents a humanoid robotic arms controlled by tracking the human skeleton movement in real-time using Kinect upper limbbody tracking. Using Kinect tracking algorithm, the positions of upper limb arms of the body to the wrist in 3D space can be estimated by processing depth images from the Kinect. An extraction of 3D co-ordinates of the user's both arm in real-time then Arduino microcontroller is transferring the data between both of computer and the humanoid robotic arm. This method provides a way to send movement task to the humanoid robotic manipulator instead of sending the end position motion like gesture-based approaches and this method has been tested in detect, tracking and following the movement of human skeleton gesture. Designing complete prototype of a humanoid robotic arms with 4DOF three joints in shoulder and one elbow joint to the wrist that look like the Human arm Structure, Appearance and Action that represent human arm movement performed by the humanoid robotic arm. The error was and response time result generated is small (less than 4.6% and 105 ms).

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