复杂环境下基于立体视觉的机器人运动规划与协商选择机制

Ming Bai, Wei Wang, Yan Zhuang
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引用次数: 0

摘要

提出了一种用于混合运动规划的交互机制和模块化方法。通过协商候选人与反应性评价的反馈协商,设计了一种双向互动。审议模块构造了一个具有切换控制集的多层状态格。此外,启发式多任务并行算法有效地生成理想路径。反应模块设计了一个分层结构,以整合反应优化和情境依赖调整。基于流形相关性,提出了分段标准,而不是单一功能,以满足规划的不同阶段。大量的实验验证了该方法在复杂环境下的有效性、可靠性和鲁棒性。
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Stereovision-based robot motion planning with negotiation-selection mechanism in complex environments
An interactive mechanism and modular approaches are proposed for hybrid motion planning. A bidirectional interaction is designed by deliberative candidates negotiating with the feedback on reactive evaluation. The deliberative module constructs a multilayer state lattice with switching control sets. Furthermore, a heuristic multitask-parallel algorithm efficiently generates desirable paths. The reactive module designs a hierarchical structure to integrate reaction optimisation and situation-dependent adjustment. Based on manifold correlations, piecewise criteria rather than a single function are proposed to cater for different stages of planning. Extensive experiments verify the efficacy, reliability and robustness of the approach in complex environments.
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来源期刊
International Journal of Vehicle Autonomous Systems
International Journal of Vehicle Autonomous Systems Engineering-Automotive Engineering
CiteScore
1.30
自引率
0.00%
发文量
0
期刊介绍: The IJVAS provides an international forum and refereed reference in the field of vehicle autonomous systems research and development.
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