Aiming at the problem that traditional methods cannot meet the problem of synchronous positioning of multi -mobile robots in different motion states, a synchronous positioning method of multi -mobile robots based on v...
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Aiming at the problem that traditional methods cannot meet the problem of synchronous positioning of multi -mobile robots in different motion states, a synchronous positioning method of multi -mobile robots based on visualsimultaneouslocalization and mapping (SLAM) algorithm is proposed. Analyze the general model of SLAM problem, realize visual SLAM feature detection through scale invariant feature transform algorithm, and match image features based on active vision. A multi -mobile robot motion state estimation model is constructed, an octree model is used to construct a multi -robot synchronous localization map, and the camera pose tracking is realized by using the oriented fast accelerated segment test and rotated binary robust independent elementary features points that are not in the target bounding box. The three-dimensional points in the environment recovered by visual SLAM separate the background target and the moving target, and match the corresponding target in the previous frame through the feature to realize the synchronous positioning of the multi -mobile robot. The experimental results show that the method can realize the synchronous positioning of multi -robots under the state of multi -robot linear motion, curvilinear motion and mixed motion, and the positioning accuracy is high.
In hw/sw co-design FPGAs are being used in order to accelerate existing solutions so they meet real-time constraints. As they consume less power than a standard microprocessor and provide powerful parallel data proces...
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ISBN:
(纸本)9781479959440
In hw/sw co-design FPGAs are being used in order to accelerate existing solutions so they meet real-time constraints. As they consume less power than a standard microprocessor and provide powerful parallel data processing capabilities, they remain a highly optimizable tool and object of research within an embedded system. In this paper we present an efficient architecture for matrix multiplication accelerator conceived as a systolic array co-processor to IBM's PPC440 processor on Virtex5 XC5VFX70T FPGA. Our design is afterwards synthesized and wired as a large-scale matrix multiplier required for an embedded version of a visualsimultaneouslocalization and mapping (SLAM) algorithm based on Extended Kalman Filter (EKF). This algorithm is implemented entirely as a System On a programmable Chip (SoC) design on the FPGA;an EKF epoch is executed at least 7.3 times faster than the pure software implementation, maintaining and correcting 20 points in the map. This optimization permits an EKF block throughput to be increased from 6.07Hz to 44.39Hz, which exceeds our real-time constraint of 30Hz.
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