Safe grasping with multi-link fingers based on force sensing

Sadigh, Mohammad Jafar; Ahmadi, Habib

doi:10.1109/robio.2009.5420425

Cited by 6 publications

(12 citation statements)

References 22 publications

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“…(Nagata, Oosaki, Kakikura, & Tsukune, 1998) presented a grasping system based on force and torque feedback that senses when the humans has a stable grasp on the object, after which the robot can release the object. (Sadigh & Ahmadi, 2009) presented a robotic grasping controller inspired by human grasping to grasp an object with minimal normal forces while ensuring the object does not slip.…”

Section: Handover Behaviors For Robotsmentioning

confidence: 99%

Towards Seamless Human-Robot Handovers

Strabala

Lee

Dragan

et al. 2013

JHRI

223

147

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A handover is a complex collaboration, where actors coordinate in time and space to transfer control of an object. This coordination comprises two processes: the physical process of moving to get close enough to transfer the object, and the cognitive process of exchanging information to guide the transfer. Despite this complexity, we humans are capable of performing handovers seamlessly in a wide variety of situations, even when unexpected. This suggests a common procedure that guides all handover interactions. Our goal is to codify that procedure. To that end, we first study how people hand objects to each other in order to understand their coordination process and the signals and cues that they use and observe with their partners. Based on these studies, we propose a coordination structure for human-robot handovers that considers the physical and social-cognitive aspects of the interaction separately. This handover structure describes how people approach, reach out their hands, and transfer objects while simultaneously coordinating the what, when, and where of handovers: to agree that the handover will happen (and with what object), to establish the timing of the handover, and to decide the configuration at which the handover will occur. We experimentally evaluate human-robot handover behaviors that exploit this structure, and offer design implications for seamless human-robot handover interactions.

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Section: Handover Behaviors For Robotsmentioning

confidence: 99%

Towards Seamless Human-Robot Handovers

Strabala

Lee

Dragan

et al. 2013

JHRI

223

147

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show abstract

“…In comparison, due to the uncertainty of the control parameters and existence of the disturbances on the robots and the environment, the convergence of the control outputs in the known case control algorithm is poor relative to the unknown case algorithm (Figs 4 to 6) which confirms the effectiveness of the control methodology presented in section (3.2). Hence, it is obvious from the results that the control signals (21) and (22) are robust against the uncertainties in the environment and grasped object and the robots and environmental disturbances.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…After substituting (21) into (16), the dynamic equation of the motion subsystem closed-loop error (26) is obtained. The force control subsystem closed-loop error (27) is also achieved by putting (22) into (17) …”

Section: The Unknown System Casementioning

confidence: 99%

A robust adaptive hybrid force/position control scheme of two planar manipulators handling an unknown object interacting with an environment

Mohajerpoor

Rezaei

Talebi

et al. 2011

Proceedings of the Institution of Mechanical Engineers, Part I:

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This paper presents a robust hybrid force/position control scheme of two cooperative manipulators handling an unknown object interacting with an unknown environment. The uncertainty of the object is considered in the weight, length, and the position of centre of mass (COM). The environment is assumed to have an unknown but high stiffness. A hybrid force/position control algorithm is designed for the known system and environment case. The exponential convergence of the position and the interaction force with the environment is proved using the Lyapunov direct method. Similarly, in the unknown object and environment case, and in the presence of bounded disturbances on the robots and the object, an adaptive sliding mode hybrid force/position control scheme is designed. The asymptotic convergence of the object's position and the constraint force is guaranteed using the proposed control methodology. The internal forces and moments between the object and robots are controlled independently of the object's motion and environmental interaction forces. Simulation results confirm the performance and effectiveness of the suggested control methodologies.

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“…Consequently, many state-of-the art techniques in robotic grasping and manipulation exploit the feedback capabilities of many different kinds of finger sensors. For instance, contemporary strategies rely heavily on measuring contact forces [65][66][67][68][69][70]. Finger sensors can provide this information through sensory layouts such as load cells, barometers, accelerometers, electrodes, hydrophones, cameras, or some combination thereof.…”

Section: Robot-gripper/hand Calibrationmentioning

confidence: 99%

Tools for Robotics in SME Workcells: Challenges and Approaches for Calibration and Registration

Marvel¹,

Messina²,

Antonishek³

et al. 2015

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An overview of the challenges associated with robot workcell calibration and registration is presented, with a particular focus on the challenges faced by small-and medium-sized manufacturing enterprises (SMEs). Considerations for the barriers to integrating systemsof-systems workcells are described, and the proposed solutions from literature are presented. We discuss the impacts that calibration and registration have on many common robot applications, and highlight specific use cases of robot-sensor and robot-robot system registration.

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Safe grasping with multi-link fingers based on force sensing

Cited by 6 publications

References 22 publications

Towards Seamless Human-Robot Handovers

Towards Seamless Human-Robot Handovers

A robust adaptive hybrid force/position control scheme of two planar manipulators handling an unknown object interacting with an environment

Tools for Robotics in SME Workcells: Challenges and Approaches for Calibration and Registration

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