Model Based Visual Servoing Tasks with an Autonomous Humanoid Robot

Moughlbay, Amine Abou; Cervera, Enric; Martinet, Philippe

doi:10.1007/978-3-642-35485-4_12

Cited by 7 publications

(4 citation statements)

References 19 publications

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“…For model-based visual servoing, image measurements can be utilized to calculate camera poses directly, which are based on apriori known three dimensional (3D) model of target objects (Moughlbay et al 2013;Cherubini et al 2008;Drummond and Cipolla 2002) or structured workspace (Caron et al 2014). Depending on object detection (Andreopoulos and Tsotsos 2013;Zhang et al 2019a;Gupta et al 2017) and apriori textured model (Desai et al 2011), the relative pose of the camera to objects can be obtained.…”

Section: Model-based Approachesmentioning

confidence: 99%

A survey on visual servoing for wheeled mobile robots

Wang

et al. 2021

Int J Intell Robot Appl

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Owing to advantages of large workspace and flexible movement, wheeled mobile robots are widely applied in industry. With vision module for environment perception, visual servoing of wheeled mobile robots has been one of the hottest research topics in robotic fields. Due to different demands for various applications and specific properties of the system, many challenges are faced for designing visual servoing control strategies. In this paper, development of visual servoing for mobile robots is elaborated in visual and control modules, respectively. The vision module along with various uncertainties are analyzed, which provides feedback signals for the servo controller, thus associating the image space with the motion space for further control. Moreover, motion controllers are devised under various constraints for different objectives, such as pose regulation and trajectory tracking. Research trends are discussed to show further focus of visual servoing of mobile robots.

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Section: Model-based Approachesmentioning

confidence: 99%

A survey on visual servoing for wheeled mobile robots

Wang

et al. 2021

Int J Intell Robot Appl

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“…Given the walk style of the robot, the solution involved the cancellation of the oscillatory contribution to the control signal (also called the sway motion). A work by Moughlbay et al [15] has considered approaching tasks with the robot Nao. In both studies, in order to handle the image noise, the tracking technique by Comport et al [5] was employed.…”

Section: Related Workmentioning

confidence: 99%

Sensory-Motor Anticipation and Local Information Fusion for Reliable Humanoid Approach

Chame

Chevallereau

2016

New Trends in Medical and Service Robots

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The possibility of developing increasingly sophisticated robots, and the availability of cloud-connected resources, have boosted the interest in the study of real world applications of service robotics. However, in order to operate under natural or less structured conditions, and given the information processing bottleneck and the reactivity required for a secure execution of the task, it is desirable that the agent can exploit more efficiently the local information available, so that being more autonomous, and relying less on remote computation. This study explores a strategy for obtaining reliable approach tasks. It considers the anticipation of perception, by taking into account the statistical regularities and the information redundancies induced in the sensorymotor coupling. From an initial perception of the object assisted by remote computation, contextual features are defined for capturing bodily sensations emerging in the task. The observations based on proprioceptive and visual data are fused in a Bayesian Network, which is in charge of assessing the saliency during the object approach, thus constituing a local discriminative processing of the object. The strategy proposed reduces dependency on context-free models of behavior, while providing an estimate on the degree of confidence in the progress of the task.

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“…To treat this problem, the compensation for the head's motion by taking advantage of the kinematic and geometric models of the robot has been attempted; such as, a virtual camera has been defined to cancel the sway motion in the visual features for continuous visual servoing (Dune et al, 2010). Though, considerable delays may be involved in the vision processing; due to digital image treatment and video data transference from the on-board camera to the computer system (Moughlbay et al, 2013). These delays can restrict the applications of real-time visual servoing techniques in closed-loop.…”

Section: Related Workmentioning

confidence: 99%

Embodied Localization in Visually-guided Walk of Humanoid Robots

Chame

Chevallereau

2014

Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics

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International audienceHumanoid robots are conceived to resemble the body and comportment of the human beings. Among the behavior repertoire, the possibility of executing visually-guided tasks is crucial for individual adaptation and relies on the on-board sensory system. However, the research on walk and localization is far from conclusive. Given the difficulties in the processing of the visual feedback, some studies have treated the problem by placing external sensors on the environment; thus neglecting the corporal metaphor. Others, despite exploring on-board solutions; have relied on an extensive model of the environment, thus considering the system as an information processing unit, abstracted from a body. This work presents a methodology to achieve embodied localization to serve visually-guided walk. The solution leans on robust segmentation from monocular vision, ego-cylindrical localization, and minimal knowledge about stimuli in the environment

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Model Based Visual Servoing Tasks with an Autonomous Humanoid Robot

Cited by 7 publications

References 19 publications

A survey on visual servoing for wheeled mobile robots

A survey on visual servoing for wheeled mobile robots

Sensory-Motor Anticipation and Local Information Fusion for Reliable Humanoid Approach

Embodied Localization in Visually-guided Walk of Humanoid Robots

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