207 research outputs found

    Efficient and secure real-time mobile robots cooperation using visual servoing

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    This paper deals with the challenging problem of navigation in formation of mobiles robots fleet. For that purpose, a secure approach is used based on visual servoing to control velocities (linear and angular) of the multiple robots. To construct our system, we develop the interaction matrix which combines the moments in the image with robots velocities and we estimate the depth between each robot and the targeted object. This is done without any communication between the robots which eliminate the problem of the influence of each robot errors on the whole. For a successful visual servoing, we propose a powerful mechanism to execute safely the robots navigation, exploiting a robot accident reporting system using raspberry Pi3. In addition, in case of problem, a robot accident detection reporting system testbed is used to send an accident notification, in the form of a specifical message. Experimental results are presented using nonholonomic mobiles robots with on-board real time cameras, to show the effectiveness of the proposed method

    Challenges and Solutions for Autonomous Robotic Mobile Manipulation for Outdoor Sample Collection

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    In refinery, petrochemical, and chemical plants, process technicians collect uncontaminated samples to be analyzed in the quality control laboratory all time and all weather. This traditionally manual operation not only exposes the process technicians to hazardous chemicals, but also imposes an economical burden on the management. The recent development in mobile manipulation provides an opportunity to fully automate the operation of sample collection. This paper reviewed the various challenges in sample collection in terms of navigation of the mobile platform and manipulation of the robotic arm from four aspects, namely mobile robot positioning/attitude using global navigation satellite system (GNSS), vision-based navigation and visual servoing, robotic manipulation, mobile robot path planning and control. This paper further proposed solutions to these challenges and pointed the main direction of development in mobile manipulation

    Visual Servoing for Nonholonomically Constrained Three Degree of Freedom Kinematic Systems

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    This paper addresses problems of robot navigation with nonholonomic motion constraints and perceptual cues arising from onboard visual servoing in partially engineered environments. We propose a general hybrid procedure that adapts to the constrained motion setting the standard feedback controller arising from a navigation function in the fully actuated case. This is accomplished by switching back and forth between moving down and across the associated gradient field toward the stable manifold it induces in the constrained dynamics. Guaranteed to avoid obstacles in all cases, we provide conditions under which the new procedure brings initial configurations to within an arbitrarily small neighborhood of the goal. We summarize simulation results on a sample of visual servoing problems with a few different perceptual models. We document the empirical effectiveness of the proposed algorithm by reporting the results of its application to outdoor autonomous visual registration experiments with the robot RHex guided by engineered beacons

    Vision-based trajectory tracking algorithm with obstacle avoidance for a wheeled mobile robot

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    Wheeled mobile robots are becoming increasingly important in industry as means of transportation, inspection, and operation because of their efficiency and flexibility. The design of efficient algorithms for autonomous or quasi-autonomous mobile robots navigation in dynamic environments is a challenging problem that has been the focus of many researchers dining the past few decades. Computer vision, maybe, is not the most successful sensing modality used in mobile robotics until now (sonar and infra-red sensors for example being preferred), but it is the sensor which is able to give the information ā€™ā€™whatā€ and ā€™ā€™whereā€ most completely for the objects a robot is likely to encounter. In this thesis, we deal with using vision system to navigate the mobile robot to track a reference trajectory and using a sensor-based obstacle avoidance method to pass by the objects located on the trajectory. A tracking control algorithm is also described in this thesis. Finally, The experimental results are presented to verify the tracking and control algorithms

    Vision-Based, Distributed Control Laws for Motion Coordination of Nonholonomic Robots

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    Methods for visual servoing of robotic systems: A state of the art survey

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    U ovom preglednom radu su prikazane metode vizuelnog upravljanja robotskih sistema, sa primarnim fokusom na mobilne robote sa diferencijalnim pogonom. Analizirane su standardne metode vizuelnog upravljanja bazirane na (i) greÅ”kama u parametrima slike (engl. Image-Based Visual Servoing - IBVS) i (ii) izdvojenim karakteristikama sa slike neophodnim za estimaciju položaja izabranog objekta (engl. Position-Based Visual Servoing - PBVS) i poređene sa novom metodom direktnog vizuelnog upravljanja (engl. Direct Visual Servoing - DVS). U poređenju sa IBVS i PBVS metodama, DVS metod se odlikuje viÅ”om tačnoŔću, ali i manjim domenom konvergencije. Zbog ovog razloga je DVS metod upravljanja pogodan za integraciju u hibridne sisteme vizuelnog upravljanja. Takođe, predstavljeni su radovi koji unapređuju sistem vizuelnog upravljanja koriŔćenjem stereo sistema (sistem sa dve kamere). Stereo sistem, u poređenju sa alternativnim metodama, omogućava tačniju ocenu dubine karakterističnih objekata sa slike, koja je neophodna za zadatke vizuelnog upravljanja. Predmet analize su i radovi koji integriÅ”u tehnike veÅ”tačke inteligencije u sistem vizuelnog upravljanja. Ovim tehnikama sistemi vizuelnog upravljanja dobijaju mogućnost da uče, čime se njihov domen primene znatno proÅ”iruje. Na kraju, napominje se i mogućnost integracije vizuelne odometrije u sisteme vizuelnog upravljanja, Å”to prouzrokuje povećanje robusnosti čitavog robotskog sistema.This paper surveys the methods used for visual servoing of robotic systems, where the main focus is on mobile robot systems. The three main areas of research include the Direct Visual Servoing, stereo vision systems, and artificial intelligence in visual servoing. The standard methods such as Image-Based Visual Servoing (IBVS) and Position-Based Visual Servoing (PBVS) are analyzed and compared with the new method named Direct Visual Servoing (DVS). DVS methods have better accuracy, compared to IBVS and PBVS, but have limited convergence area. Because of their high accuracy, DVS methods are suitable for integration into hybrid systems. Furthermore, the use of the stereo systems for visual servoing is comprehensively analyzed. The main contribution of the stereo system is the accurate depth estimation, which is critical for many visual servoing tasks. The use of artificial intelligence (AI) in visual servoing purposes has also gained popularity over the years. AI techniques give visual servoing controllers the ability to learn by using predefined examples or empirical knowledge. The learning ability is crucial for the implementation of robotic systems in a real-world dynamic manufacturing environment. Also, we analyzed the use of visual odometry in combination with a visual servoing controller for creating more robust and reliable positioning system

    Adaptive tracking control of a wheeled mobile robot via an uncalibrated camera system

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