Interaction Control of Robot Manipulators Using Force and Vision

Lippiello, Vincenzo; Siciliano, Bruno; Villani, Luigi

doi:10.1080/15599610802301599

Cited by 13 publications

(7 citation statements)

References 17 publications

(13 reference statements)

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“…To this end, many pHRI works rely on the physical contact (touch) between robot and operator [31]. More recently, to guarantee interaction even in the absence of direct contact, researchers have proposed the use of pointing gestures [32], as well as the integration of vision with force [33,34,35]. Also, in our work, interaction includes both vision and force.…”

Section: Research On Physical Human-robot Collaborationmentioning

confidence: 99%

Collaborative manufacturing with physical human–robot interaction

Cherubini¹,

Passama²,

Crosnier³

et al. 2016

Robotics and Computer-Integrated Manufacturing

466

188

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Although the concept of industrial cobots dates back to 1999, most present day hybrid human-machine assembly systems are merely weight compensators. Here, we present results on the development of a collaborative human-robot manufacturing cell for homokinetic joint assembly. The robot alternates active and passive behaviours during assembly, to lighten the burden on the operator in the first case, and to comply to his/her needs in the latter. Our approach can successfully manage direct physical contact between robot and human, and between robot and environment. Furthermore, it can be applied to standard position (and not torque) controlled robots, common in the industry. The approach is validated in a series of assembly experiments. The human workload is reduced, diminishing the risk of strain injuries. Besides, a complete risk analysis indicates that the proposed setup is compatible with the safety standards, and could be certified.

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Section: Research On Physical Human-robot Collaborationmentioning

confidence: 99%

Collaborative manufacturing with physical human–robot interaction

Cherubini¹,

Passama²,

Crosnier³

et al. 2016

Robotics and Computer-Integrated Manufacturing

466

188

View full text Add to dashboard Cite

show abstract

“…A camera frame O c - x c y c z c attached to the camera and an object frame O o - x o y o z o attached to the object are considered. Then, the transformation of the object’s feature point P from the object frame to the camera frame is defined as (Lippiello et al , 2008): …”

Section: System Modelmentioning

confidence: 99%

“…As a robot is expected to be more autonomous and flexible to accomplish complicated tasks in unknown environments, the need to integrate a number of different sensors into the robot system becomes increasingly important. Consequently, multisensor-based control scheme, which can compensate for changes in the environment and uncertainties in the dynamic models without explicit human intervention or reprogramming, has been proposed and developed (Xiao et al , 2000; Lippiello et al , 2008; Long et al , 2014). In various sensors, the force and vision sensors are very widely used.…”

Section: Introductionmentioning

confidence: 99%

Hybrid position/force control of 6-dof hydraulic parallel manipulator using force and vision

Gao

Cong

Liu

et al. 2016

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Purpose The purpose of this paper is to propose a hybrid position/force control scheme using force and vision for docking task of a six degrees of freedom (6-dof) hydraulic parallel manipulator (HPM). Design/methodology/approach The vision system consisted of a charge-coupled device (CCD) camera, and a laser distance sensor is used to provide globe relative position information. Also, a force plate is used to measure local contact forces. The proposed controller has an inner/outer loop structure. The inner loop takes charge of tracking command pose signals from outer loop as accurate as possible, while the outer loop generates the desired tracking trajectory according to force and vision feedback information to guarantee compliant docking. Several experiments have been performed to validate the performance of the proposed control scheme. Findings Experiment results show that the system has good performance of relative position tracking and compliant contact. In whole docking dynamic experiment, the amplitudes of contact forces are well controlled within 300 N, which can meet perfectly the requirement of the amplitude being not more than 1,000 N. Originality/value A hybrid position/force control scheme using force and vision is proposed to make a 6-dof HPM dock with a moving target object compliantly.

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“…In this context, the robot must infer the user intention, to interact more naturally, from the human perspective [8,9,10]. To this end, both visual (e.g., based on Microsoft Kinect TM [11]) and force feedback, have been used [12,13,14,15,16]. Generally, we believe that direct sensor-based methods, such as visual servoing [17], provide better solutions, for intuitive HRI, than planning techniques, requiring a priori models of the environment and agents [18].…”

Section: Introductionmentioning

confidence: 99%

A unified multimodal control framework for human–robot interaction

Cherubini

Passama

Fraisse

et al. 2015

Robotics and Autonomous Systems

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In human-robot interaction, the robot controller must reactively adapt to sudden changes in the environment (due to unpredictable human behaviour). This often requires operating different modes, and managing sudden signal changes from heterogeneous sensor data. In this paper, we present a multimodal sensor-based controller, enabling a robot to adapt to changes in the sensor signals (here, changes in the human collaborator behaviour). Our controller is based on a unified task formalism, and in contrast with classical hybrid visionforce-position control, it enables smooth transitions and weighted combinations of the sensor tasks. The approach is validated in a mock-up industrial scenario, where pose, vision (from both traditional camera and Kinect), and force tasks must be realized either exclusively or simultaneously, for human-robot collaboration.

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Interaction Control of Robot Manipulators Using Force and Vision

Cited by 13 publications

References 17 publications

Collaborative manufacturing with physical human–robot interaction

Collaborative manufacturing with physical human–robot interaction

Hybrid position/force control of 6-dof hydraulic parallel manipulator using force and vision

A unified multimodal control framework for human–robot interaction

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