Achieving efficient and stable comanipulation through adaptation to changes in human arm impedance

Lamy, Xavier; Colledani, F.; Geffard, Franck; Measson, Yvan; Morel, Guillaume

doi:10.1109/robot.2009.5152294

Cited by 45 publications

(24 citation statements)

References 11 publications

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“…Another desirable property of the robot control during interaction should be transparency [Lamy et al, 2009], e.g., in some applications, the robot should not oppose resistance to the force applied by the human operator when driving the robot, but it should rather move according to the intention of the human operator. This issue is particularly critical during co-manipulation, where an object is simultaneously held by the human and the robot.…”

Section: Stability and Transparency Of The Phrc Systemsmentioning

confidence: 99%

“…This issue has been investigated using the concept of passivity: in [Colgate and Hogan, 1988], Colgate showed that when two stable systems with passive port functions are physically coupled, stability of the coupled system is guaranteed. However, passivity leads to very conservative gain tuning and constrain the apparent endpoint inertia to remain 50% higher than its real value, which prevents many co-manipulation applications with heavy robots [Lamy et al, 2009]. It is important to note here that in robots with joint torque sensing, the torque feedback can contribute to a substantial reduction of total inertia, while staying in a passivity framework .…”

Section: Stability and Transparency Of The Phrc Systemsmentioning

confidence: 99%

“…A common way to estimate it, is via the grasping force at the interaction point, by dedicated force/torque sensors, even if in industrial applications there exists several cases where the human operator interacts directly with the payload, such as with lifting or assist devices. In [Lamy et al, 2009], the authors designed a handle for intuitive co-manipulation, where a 6-dof force/torque sensor was covered by a soft foam: when held delicately through a precision grip, the foam acts as a mechanical filter, and the system reflects low inertia; conversely, when held firmly through a power grasp, resulting from higher impedance in the arm because of muscle co-contraction [Napier, 1956], the squeezed foam does not filter, the system exhibits higher inertia, the gains are lowered and the system remains stable.…”

Section: Lessons From Human Motor Controlmentioning

confidence: 99%

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Progress and prospects of the human–robot collaboration

et al. 2017

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Recent technological advances in hardware design of the robotic platforms enabled the implementation of various control modalities for improved interactions with humans and unstructured environments. An important application area for the integration of robots with such advanced interaction capabilities is human-robot collaboration. This aspect represents high socio-economic impacts and maintains the sense of purpose of the involved people, as the robots do not completely replace the humans from the work process. The research community's recent surge of interest in this area has been devoted to the implementation of various methodologies to achieve intuitive and seamless humanrobot-environment interactions by incorporating the collaborative partners' superior capabilities, e.g. human's cognitive and robot's physical power generation capacity. In fact, the main purpose of this paper is to review the state-of-theart on intermediate human-robot interfaces (bi-directional), robot control modalities, system stability, benchmarking and relevant use cases, and to extend views on the required future developments in the realm of human-robot collaboration.Arash Ajoudani is with HRI

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Section: Stability and Transparency Of The Phrc Systemsmentioning

confidence: 99%

Section: Stability and Transparency Of The Phrc Systemsmentioning

confidence: 99%

Section: Lessons From Human Motor Controlmentioning

confidence: 99%

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Progress and prospects of the human–robot collaboration

et al. 2017

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“…In order for the robots to be capable to interact and collaborate with humans, it should consider certain requirements in the mechanical structure design, its hardware, and the control schemes [10]. These robots typically require lightweight, compliant, and flexible mechanical structures.…”

Section: Introductionmentioning

confidence: 99%

Adaptive threshold for robot manipulator collision detection using fuzzy system

et al. 2020

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The topic of collision detection was recently addressed in the literature due to the demand of safe human-robot collaboration. Several methods have been proposed for this task; some of these methods use external sensors while others do not (sensor-less). The classical sensor-less method is attained by setting a threshold to detect the change in torque/ current. This method is simple and applicable for real-time implementation and does not require any prior information on the robot dynamical model. However, any wrong choices on the threshold value might lead up to undesirable performance. Therefore, in this paper we propose an evolved solution using the classical method while operating the fuzzy logic system. The enhanced system results in an adaptive collision threshold based on the variation of the robots speed and acceleration. The system is presented in this paper along with the experimental setup and the implementation steps.

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“…In [13], a cascaded loop using proportional (P) correction for the velocity loop and proportional and integral (PI) correction for the force loop is proposed. Then the equivalent impedance of the full system is calculated -it is equivalent to a apparent mass proportional to the integral correction of the system.…”

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confidence: 99%