An eye-in-hand stereo visual servoing for tracking and catching moving objects

Mohebbi, Abolfazl; Keshmiri, Mohammad; Xie, Wen

doi:10.1109/chicc.2014.6896439

Cited by 14 publications

(15 citation statements)

References 20 publications

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“…In the case of a traditional proportional controller, the input to the robot controller u c is designed by lettinġ e = −λ e u c = −λ J e + e (25) where J e is the image interaction matrix which relates the time variation of error e and the camera velocity and J e + is the Moore-Penrose pseudo-inverse of the interaction matrix. λ is the proportional gain for the visual controller.…”

Section: Visual Servoing Controlmentioning

confidence: 99%

“…where the term (∂ e/∂t) represents the time variation of e caused by the target motion which is considered to have a constant velocity. In our case we assume that the vision system is composed of a stereo vision system with two parallel cameras which are perpendicular to the baseline [26,27]. The focal points of two cameras are apart at distance b/2 with respect to origin of sensor frame C on the baseline which means the origin of the camera frame, is in the centre of these points.…”

Section: Visual Servoing Controlmentioning

confidence: 99%

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Design of a Vision Guided Mechatronic Quadrotor System Using Design for Control Methodology

Mohebbi

Achiche

Baron

2016

Transactions of the Canadian Society for Mechanical Engineering

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Designing mechatronic systems is known to be both a very complex and tedious process. This complexity is due to the high number of system components, their multi-physical aspects, the couplings between different engineering domains and the interacting and/or conflicting design objectives. Due to this inherent complexity and the dynamic coupling between subsystems of mechatronic systems, a systematic and multi-objective design approach is needed to replace the traditionally used sequential design methods. The traditional approaches usually lead to functional but non optimal designs solutions. In this paper, and based on an integrated and concurrent design approach called “Design-for-Control” (DFC), a quadrotor UAV equipped with a stereo visual servoing system is used as a case study. After presenting the dynamics and the control model of the Quadrotor UAV and its visual servoing system, the design process has been performed in four iterations and as expected, the control performance of the system has been significantly improved after finishing the final design iteration.

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Section: Visual Servoing Controlmentioning

confidence: 99%

Section: Visual Servoing Controlmentioning

confidence: 99%

Design of a Vision Guided Mechatronic Quadrotor System Using Design for Control Methodology

Mohebbi

Achiche

Baron

2016

Transactions of the Canadian Society for Mechanical Engineering

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“…3 shows a schematic diagram of the aforementioned robotic visual servoing system and its components. Figure 4: A robotic visual servoing system and its components [24], (a) 6-DOF robot manipulator and the moving object, (b) Visual servoing control system…”

Section: Case Study: Design Of a Robotic Visual Servoing Systemmentioning

confidence: 99%

Fuzzy Decision Making for Conceptual Design of a Visual Servoing System Using Mechatronic Multi-Criteria Profile (MMP)

Mohebbi

Achiche

Baron

et al. 2014

Volume 11: Systems, Design, and Complexity

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Mechatronic systems are of increased importance in engineering and their relevance goes hand in hand with the increasing complexity of the tasks they perform. Due to the inherent complexity of mechatronic systems, a concurrent systematic and multi-objective design thinking methodology is crucial to replace the often used sequential design approach that tends to deal with the different domains separately. In this research we present a new multi-criteria profile (MMP) for mechatronic system performance evaluation in the stage of conceptual design. Based on the assessed MMP for each of generated design concepts and using a method of aggregation for interacting criteria, a global performance index will be calculated. Best mechatronic configurations are determined by maximizing this performance index. In the presented paper two nonlinear fuzzy integrals called 2-additive Choquet and Sugeno will be used for the aggregation of criteria and fitting the intuitive requirements for decision-making in the presence of interacting criteria. Finally, the effectiveness of the proposed design method alongside each of the decision making models will be validated via a case study of designing a robotic visual servoing system. The comparative simulation results for the overall system performance will also be presented for both cases of using Choquet and Sugeno integrals.

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“…Stereo visual servoing has many advantages over the classical monocular visual servoing approaches. For example, the depth information can be recovered without using any geometrical model of the observed object [12]. It should be noted that in classical image-based visual servoing, this information is needed for the computation of the image interaction matrix.…”

Section: Introductionmentioning

confidence: 99%