Current Issue : January - March Volume : 2017 Issue Number : 1 Articles : 5 Articles
Robot manipulators enable large-scale factory automation of simple and repeated\ntasks. Each manipulation is the result of the robot design and the command inputs provided\nby the operator. In this study, we focus on the accuracy improvement of practical\nrobot manipulation under uncertainty, resulting in path-specific error values. Existing\ntechniques for reducing the errors use high-precision sensors and measurements to\nobtain the values of a manipulator to provide feedback control. Instead of compensating\nerrors in operation, this study designs a calibration table to obtain the error value\nfor a designated path. This error is then used to adjust important parameters in the kinematic\nclosed chain models of a manipulators via optimization. The proposed method\nreduces the cost and the dependence on the calibration process. Experimental results\nshow that the overall accuracy of the manipulator is improved. The proposed method\ncan also be extended to develop the optimal robotic manipulation planning and reliability\nassessment in the future....
This paper investigates cooperative flocking control design with connectivity preserving mechanism. During flocking, interagent\ndistance is measured to determine communication topology of the flocks. Then, cooperative flocking motion is built based on\ncooperative artificial potential field with connectivity preserving mechanism to achieve the common flocking objective.The flocking\ncontrol input is then obtained by deriving cooperative artificial potential field using control Lyapunov function. As a result, we\nprove that our flocking protocol establishes group stabilization and the communication topology of multiagent flocking is always\nconnected....
Locating a fire inside of a structure that is not in the direct field of view of the robot has been researched for intelligent firefighting\nrobots. By classifying fire, smoke, and their thermal reflections, firefighting robots can assess local conditions, decide a proper\nheading, and autonomously navigate toward a fire. Long-wavelength infrared camera images were used to capture the scene\ndue to the camera�s ability to image through zero visibility smoke. This paper analyzes motion and statistical texture features\nacquired from thermal images to discover the suitable features for accurate classification. Bayesian classifier is implemented to\nprobabilistically classify multiple classes, and a multiobjective genetic algorithm optimization is performed to investigate the\nappropriate combination of the features that have the lowest errors and the highest performance. The distributions of multiple\nfeature combinations that have 6.70% or less error were analyzed and the best solution for the classification of fire and smoke was\nidentified....
In this paper, we have dealt with the problem to transport large heavy objects using a group of small mobile robots.\nGenerally, payload of the robot, the maximum weight of the object that the robot can operate, is very small and they\ncannot transport heavy objects with standard coordinated grasping methodology. This paper considers a method\nof transporting an object using handcarts by tilting the object to load it on the handcarts. To resolve the problem\nof avoiding overturning of the object by the robots and sliding of the handcart while tilting the object, an outrigger\ndevice is used to prevent the first problem of tilting, and a handcart locking device is used to prevent the second\nproblem of sliding. As both devices need to be used only when necessary, a mechanism that can fix and release the\ndevices according to situations is newly designed. Two robots were trial fabricated: an object-tilting robot equipped\nwith an outrigger mechanism and a handcart transport robot to handle the handcarts. Both robots are smaller\nthan 0.6 m Ã?â?? 0.6 m with payload of 2.5 kg. They are equipped with a handcart mechanism that can be locked and\nunlocked. The use of the coordination and lock mechanisms by these robots has realized transport of objects approximately\n1 m high and weighing approximately 35 kg and demonstrated the effectiveness of the proposed system in a\nreal-world environment where robot mechanism errors, mobility errors, and observation errors occur....
This article concentrates on open-source implementation on flying object detection in cluttered scenes. It is of\nsignificance for ground stereo-aided autonomous landing of unmanned aerial vehicles. The ground stereo vision\nguidance system is presented with details on system architecture and workflow. The Chanââ?¬â??Vese detection algorithm\nis further considered and implemented in the robot operating systems (ROS) environment. A data-driven interactive\nscheme is developed to collect datasets for parameter tuning and performance evaluating. The flying vehicle outdoor\nexperiments capture the stereo sequential images dataset and record the simultaneous data from pan-and-tilt unit,\nonboard sensors and differential GPS. Experimental results by using the collected dataset validate the effectiveness of\nthe published ROS-based detection algorithm....
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