The invention relates to a quadruped robot stair detection method based on adaptive granularity tuning, and belongs to the field of intelligent robots. The method at least comprises the following steps: acquiring environment data through a camera and a laser radar of a robot, and carrying out preprocessing and granularity layering on the environment data; extracting features of different granularities by adopting an adaptive granularity tuning strategy, and carrying out weighted fusion on the features of different granularities to obtain fused features; the fusion features are input into a multi-task learning framework to estimate a plurality of key parameters of the stairs, a joint loss function and a self-adaptive weighting mechanism are adopted to allocate loss weights of tasks, correlation between the tasks is measured based on a gradient task correlation analysis method, and finally a stair detection result is output; and continuously feeding back and correcting a stair detection result through a robot posture and stair parameter feedback model. According to the method, the fusion mode of the multi-granularity features is adaptively adjusted according to environment and task requirements, the detection result is corrected according to feedback, and the method can adapt to a complex stair detection environment.
本发明涉及一种基于适应性粒度调谐的四足机器人楼梯检测方法,属于智能机器人领域。其至少包括:通过机器人的相机和激光雷达获取环境数据并对环境数据进行预处理和粒度分层;采用适应性粒度调谐策略提取不同粒度的特征,将不同粒度的特征加权融合得到融合特征;将融合特征输入多任务学习框架对楼梯的多个关键参数进行估计,其中,采用联合损失函数及自适应加权机制分配个任务的损失权重,并基于梯度的任务相关性分析方法衡量任务间的相关性,最终输出楼梯检测结果;再通过机器人姿态及楼梯参数反馈模型不断反馈修正楼梯检测结果。本发明根据环境和任务需求自适应地调整多粒度特征的融合方式,并根据反馈修正检测结果,能够适应复杂楼梯检测环境。
Quadruped robot stair detection method based on adaptive granularity tuning
基于适应性粒度调谐的四足机器人楼梯检测方法
2024-12-20
Patent
Electronic Resource
Chinese
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