A Friendly Beast of Burden: A Human-Assistive Robot for Handling Large Payloads

Gosselin, Clément; Laliberté, Thierry; Mayer-St-Onge, Boris; Foucault, Simon; Lecours, Alexandre; Duchaine, Vincent; Paradis, Noemie; Gao, Dehua; Menassa, Roland

doi:10.1109/mra.2013.2283651

Cited by 52 publications

(68 citation statements)

References 11 publications

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“…This observation matches the pHRI result of implementing SDVAC in human/manipulator interaction in [27,37]. existing literature [19,25,27,[30][31][32][33]37]. The viscosity of CAC is conservatively designed for the worst-case stiffness, whereas the viscosity of SDVAC is always smaller than or equal to (in the worst case) the viscosity of CAC.…”

Section: Possible Improvements On the Experimentssupporting

confidence: 84%

Stability and Variable Admittance Control in the Physical Interaction with a Mobile Robot

Wang¹,

Patota²,

Buondonno³

et al. 2015

Int. j. adv. robot. syst.

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Admittance controllers have been widely implemented in physical human/robot interaction (pHRI). The stability criteria and the parameter adaptation methods for admittance control have been well-studied. However, the established methods have mainly focused on human/ manipulator interaction, and cannot be directly extended to mobile robot-based pHRI, in which the nonlinearity cannot be cancelled by feedback linearizations and the measurements of the relative human/robot position and orientation are usually lacking. In this paper, we study the pHRI between a human user and a mobile robot under admittance control. We develop a robotic system which can measure the relative chest/ankle positions of the human user with respect to the robot. Using the measured human position, a human frame admittance controller is proposed to remove the nonlinearity in the system dynamics. Based on the human-frame admittance control, a stability criterion is derived. By using a human arm stiffness estimator along with the derived stability criterion, a stiffness-based variable admittance controller is designed. The effectiveness of the proposed methods in improving the pHRI performance is tested and supported by simulations and experimental results.

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Section: Possible Improvements On the Experimentssupporting

confidence: 84%

Stability and Variable Admittance Control in the Physical Interaction with a Mobile Robot

Wang¹,

Patota²,

Buondonno³

et al. 2015

Int. j. adv. robot. syst.

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show abstract

“…The ergonomic reasons might be that intuitiveness, reflection of user's intention through input forces, haptic engagement, interactivity, information sharing, guidance to motion through sensing, and naturalness might increase when closeness between human hands and force sensors increased for the separate force sensors case. 3,4,10 We believe that lower load forces produce lower accelerations (Table 7) and better pHRI (Table 6) for the separate force sensors case over the common force sensor case. The f h(peak) and f h(excess) were proportional to object sizes.…”

Section: Analysis Of Kinematicsmentioning

confidence: 94%

“…Most physical human-robot interactions (pHRIs) follow impedance controls, 8 but we derive controls for the PARS differently based on equation (4) as in Figure 2 that may fall within the admittance control (force is input and displacement is output), 8 integrated with velocity control 10 and position feedback. 18 The commanded velocity ( _ x c ) and the position feedback are expressed in equation (5), where _ x c is the input to the servomotor, G is the feedback gain, and the servomotor produces the actuating force according to _ x c .…”

Section: Weight-perception-based Dynamics Modelsmentioning

confidence: 99%

Weight-perception-based fixed and variable admittance control algorithms for unimanual and bimanual lifting of objects with a power assist robotic system

Rahman

Ikeura

2018

International Journal of Advanced Robotic Systems

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Weight-perception-based fixed admittance control algorithm and variable admittance control algorithm are proposed for unimanual and bimanual lifting of objects with a power assist robotic system. To include weight perception in controls, the mass parameter for the inertial force is hypothesized as different from that for the gravitational force in the dynamics model for lifting objects with the system. For the bimanual lift, two alternative approaches of force sensor arrangements are considered: a common force sensor and two separate force sensors between object and human hands. Computational models for power assistance, excess in load forces, and manipulation efficiency and precision are derived. The fixed admittance control algorithm is evaluated in a 1-degree-of-freedom power assist robotic system. Results show that inclusion of weight perception in controls produce satisfactory performance in terms of power assistance, system kinematics and kinetics, human-robot interactions, and manipulation efficiency and precision. The fixed admittance control algorithm is then augmented to variable admittance control algorithm as a tool of active compliance to vary the admittance with inertia instead of with gravity. The evaluation shows further improvement in the performance for the variable admittance control algorithm. The evaluation also shows that bimanual lifts outperform unimanual lifts and bimanual lifts with separate force sensors outperform bimanual lifts with a common force sensor. Then, the results are proposed to develop power assist robotic systems for handling heavy objects in industries.

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“…The software which integrates the gantry, robot arm, and robot gripper under a single controller was developed under this thrust, as well as capabilities such as the compliant control of the kinematic chain and backdrive capabilities [7,12,13]. …”

Section: Thrustmentioning

confidence: 99%