101 research outputs found

    Mobile robot transportation in laboratory automation

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    In this dissertation a new mobile robot transportation system is developed for the modern laboratory automation to connect the distributed automated systems and workbenches. In the system, a series of scientific and technical robot indoor issues are presented and solved, including the multiple robot control strategy, the indoor transportation path planning, the hybrid robot indoor localization, the recharging optimization, the robot-automated door interface, the robot blind arm grasping & placing, etc. The experiments show the proposed system and methods are effective and efficient

    Intelligent strategies for mobile robotics in laboratory automation

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    In this thesis a new intelligent framework is presented for the mobile robots in laboratory automation, which includes: a new multi-floor indoor navigation method is presented and an intelligent multi-floor path planning is proposed; a new signal filtering method is presented for the robots to forecast their indoor coordinates; a new human feature based strategy is proposed for the robot-human smart collision avoidance; a new robot power forecasting method is proposed to decide a distributed transportation task; a new blind approach is presented for the arm manipulations for the robots

    An intelligent multi-floor mobile robot transportation system in life science laboratories

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    In this dissertation, a new intelligent multi-floor transportation system based on mobile robot is presented to connect the distributed laboratories in multi-floor environment. In the system, new indoor mapping and localization are presented, hybrid path planning is proposed, and an automated doors management system is presented. In addition, a hybrid strategy with innovative floor estimation to handle the elevator operations is implemented. Finally the presented system controls the working processes of the related sub-system. The experiments prove the efficiency of the presented system

    Virtual Structure Based Formation Tracking of Multiple Wheeled Mobile Robots: An Optimization Perspective

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    Today, with the increasing development of science and technology, many systems need to be optimized to find the optimal solution of the system. this kind of problem is also called optimization problem. Especially in the formation problem of multi-wheeled mobile robots, the optimization algorithm can help us to find the optimal solution of the formation problem. In this paper, the formation problem of multi-wheeled mobile robots is studied from the point of view of optimization. In order to reduce the complexity of the formation problem, we first put the robots with the same requirements into a group. Then, by using the virtual structure method, the formation problem is reduced to a virtual WMR trajectory tracking problem with placeholders, which describes the expected position of each WMR formation. By using placeholders, you can get the desired track for each WMR. In addition, in order to avoid the collision between multiple WMR in the group, we add an attraction to the trajectory tracking method. Because MWMR in the same team have different attractions, collisions can be easily avoided. Through simulation analysis, it is proved that the optimization model is reasonable and correct. In the last part, the limitations of this model and corresponding suggestions are given

    Path Planning Based on Fuzzy Decision Trees and Potential Field

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    The fuzzy logic algorithm is an artificial intelligence algorithm that uses mathematical logic to solve to by the data value inputs which are not precise in order to reach an accurate conclusion. In this work, Fuzzy decision tree (FDT) has been designed to solve the path planning problem by considering all available information and make the most appropriate decision given by the inputs. The FDT is often used to make a path planning decision in graph theory. It has been applied in the previous researches in the field of robotics, but it still shows drawbacks in that the robot will stop at the local minima and is not able to find the shortest path. Hence, this paper combines the FDT algorithm with the potential field algorithm. The potential field algorithm provides weight to the FDT algorithm which enables the robot to successfully avoid the local minima and find the shortest path

    A 360 VR and Wi-Fi Tracking Based Autonomous Telepresence Robot for Virtual Tour

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    This study proposes a novel mobile robot teleoperation interface that demonstrates the applicability of a robot-aided remote telepresence system with a virtual reality (VR) device to a virtual tour scenario. To improve realism and provide an intuitive replica of the remote environment for the user interface, the implemented system automatically moves a mobile robot (viewpoint) while displaying a 360-degree live video streamed from the robot to a VR device (Oculus Rift). Upon the user choosing a destination location from a given set of options, the robot generates a route based on a shortest path graph and travels along that the route using a wireless signal tracking method that depends on measuring the direction of arrival (DOA) of radio signals. This paper presents an overview of the system and architecture, and discusses its implementation aspects. Experimental results show that the proposed system is able to move to the destination stably using the signal tracking method, and that at the same time, the user can remotely control the robot through the VR interface

    The high-speed rotorcraft unmanned aerial vehicle path planning based on the biogeography-based optimization algorithm

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    A three-dimensional path planning method based on the biogeography-based optimization algorithm is presented for high-speed rotorcraft unmanned aerial vehicle which has a maximum speed of 20 m/s. In this study, a novel exponential artificial potential field is used to prevent saturation, for its peculiarity of smoothness and boundness. Several parameters, which can make a large influence to the result of path planning, are picked out and used to improve the process of planning. Biogeography-based optimization algorithm is first used to optimize the parameters of artificial potential fields, for its best performance in stability and speed. The algorithm has good stability and fast operation speed, which can realize the global path planning of multi-rotor aircraft well, verified by the simulation results

    Hybrid approaches for mobile robot navigation

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    The work described in this thesis contributes to the efficient solution of mobile robot navigation problems. A series of new evolutionary approaches is presented. Two novel evolutionary planners have been developed that reduce the computational overhead in generating plans of mobile robot movements. In comparison with the best-performing evolutionary scheme reported in the literature, the first of the planners significantly reduces the plan calculation time in static environments. The second planner was able to generate avoidance strategies in response to unexpected events arising from the presence of moving obstacles. To overcome limitations in responsiveness and the unrealistic assumptions regarding a priori knowledge that are inherent in planner-based and a vigation systems, subsequent work concentrated on hybrid approaches. These included a reactive component to identify rapidly and autonomously environmental features that were represented by a small number of critical waypoints. Not only is memory usage dramatically reduced by such a simplified representation, but also the calculation time to determine new plans is significantly reduced. Further significant enhancements of this work were firstly, dynamic avoidance to limit the likelihood of potential collisions with moving obstacles and secondly, exploration to identify statistically the dynamic characteristics of the environment. Finally, by retaining more extensive environmental knowledge gained during previous navigation activities, the capability of the hybrid navigation system was enhanced to allow planning to be performed for any start point and goal point

    High-precision grasping and placing for mobile robots

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    This work presents a manipulation system for multiple labware in life science laboratories using the H20 mobile robots. The H20 robot is equipped with the Kinect V2 sensor to identify and estimate the position of the required labware on the workbench. The local features recognition based on SURF algorithm is used. The recognition process is performed for the labware to be grasped and for the workbench holder. Different grippers and labware containers are designed to manipulate different weights of labware and to realize a safe transportation
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