35 research outputs found

    Automatic goal allocation for a planetary rover with DSmT

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    In this chapter, we propose an approach for assigning aninterest level to the goals of a planetary rover. Assigning an interest level to goals, allows the rover to autonomously transform and reallocate the goals. The interest level is defined by data-fusing payload and navigation information. The fusion yields an 'interest map',that quantifies the level of interest of each area around the rover. In this way the planner can choose the most interesting scientific objectives to be analysed, with limited human intervention, and reallocates its goals autonomously. The Dezert-Smarandache Theory of Plausible and Paradoxical Reasoning was used for information fusion: this theory allows dealing with vague and conflicting data. In particular, it allows us to directly model the behaviour of the scientists that have to evaluate the relevance of a particular set of goals. This chaptershows an application of the proposed approach to the generation of a reliable interest map

    FR-SLAM: A SLAM Improvement Method Based on Floor Plan Registration

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    Simultaneous Localization and Mapping (SLAM) technology enables the construction of environmental maps and localization, serving as a key technique for indoor autonomous navigation of mobile robots. Traditional SLAM methods typically require exhaustive traversal of all rooms during indoor navigation to obtain a complete map, resulting in lengthy path planning times and prolonged time to reach target points. Moreover, cumulative errors during motion lead to inaccurate robot localization, impacting navigation efficiency.This paper proposes an improved SLAM method, FR-SLAM, based on floor plan registration, utilizing a morphology-based floor plan registration algorithm to align and transform original floor plans. This approach facilitates the rapid acquisition of comprehensive motion maps and efficient path planning, enabling swift navigation to target positions within a shorter timeframe. To enhance registration and robot motion localization accuracy, a real-time update strategy is employed, comparing the current position\u27s building structure with the map and dynamically updating floor plan registration results for precise localization. Comparative tests conducted on real and simulated datasets demonstrate that, compared to other benchmark algorithms, this method achieves higher floor plan registration accuracy and shorter time consumption to reach target positions

    Microstructural characterization and formation mechanism of abnormal segregation band of hot rolled ferrite/pearlite steel

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    AbstractIn order to further reveal the microstructural characterization and formation mechanism of abnormal segregation band of hot rolled ferrite/pearlite steel, the microstructure of this type steel was intensively studied with Scanning Auger Microprobe (SAM), etc. The results show that severe C–Mn segregation exists in the abnormal segregation band region at the center of hot rolled ferrite/pearlite steel, which results from the Mn segregation during solidification process of the continuous casting slab. The C–Mn segregation causes relative displacement of pearlite transformation curve and bainite transformation curve of C curve in the corresponding region, leading to bay-like shaped C curve. The bay-like shaped C curve creates conditions for the transformation from supercooling austenite to bainite at relatively lower cooling rate in this region. The Fe–Mn–C Atomic Segregation Zone (FASZ) caused by C–Mn segregation can powerfully retard the atomic motion, and increase the lattice reconstruction resistance of austenite transformation. These two factors provide thermodynamic and kinetic conditions for the bainite transformation, and result in the emergence of granular bainitic abnormal segregation band at the center of steel plate, which leads to lower plasticity and toughness of this region, and induces the layered fracture
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