Automated inventory management and security surveillance system using image processing techniques

Jyothsnaa, S.; Gandhe, Adwait; Deshpande, A. M.; Bodas, Sourabh

doi:10.1109/tencon.2010.5685983

Cited by 3 publications

(1 citation statement)

References 2 publications

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“…Secondly for shortest path guarantee, dRRT* ensures that the global shortest path is found, even if there are changes in the environment. It keeps optimizing the tree structure to find shorter paths [9]. While mmdRRT* can only ensure that a sub-optimal path is found because it will not be optimized after the tree structure is established.…”

Section: Path Planing Using Mmdrrt*mentioning

confidence: 99%

Logistics warehousing system shelving station route planning based on X-ARM

Feng

2024

ACE

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The need for automated control in warehouse and logistics systems has increased recently, particularly in the area of cargo storage. The use of robot arms in manufacturing is an important area for development. Multi-arm actions, including switching between multiple arms, expand the number of potential operations that numerous operators can do, but they also bring more computing hurdles. Multiple robotic arm systems must operate with careful path planning. In this study, Based on previous research papers, we propose the utilization of dRRT* and mmdRRT* algorithms for efficient path planning. The dRRT* algorithm improves exploration and convergence to an ideal path by combining the advantages of the rapidly-exploring random tree (RRT) with the optimal RRT* algorithm. To address complicated and dynamic situations, the mmdRRT* algorithm, on the other hand, uses a multi-modal distribution model. We want to improve the reliability and effectiveness of path planning for various robotic arm systems by combining these two techniques.

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Section: Path Planing Using Mmdrrt*mentioning

confidence: 99%