Robot obstacle avoidance method based on virtual scene training

Abstract

The invention discloses a robot obstacle avoidance method based on virtual scene training. The method comprises the following steps of S1, acquiring a virtual model of a robot arm, and constructing avirtual operation platform in gazebo; S2, acquiring a data set by adopting a domain randomization algorithm based on the virtual environment constructed in the S1; S3, constructing a semantic segmentation network, and training the semantic segmentation network by adopting the data set obtained in the S2 to obtain a semantic segmentation model for segmenting a mechanical arm, a human limb and a background; S4, constraining the motion trail of the mechanical arm, constructing a reward system, and constructing a reinforcement learning model in combination with a Sarsa-lamda algorithm to carry outobstacle avoidance training on the mechanical arm; and S5, migrating the semantic segmentation model and the reinforcement learning model to a ur3 mechanical arm and kinect composition system. According to the method, a virtual environment is constructed, the domain randomization is adopted in the virtual environment to obtain the sufficient data set, the semantic segmentation network with good robustness is obtained through training, and reconstruction of the trail of the mechanical arm and effective obstacle avoidance are achieved in combination with a reinforcement learning model based onSarsa-lamda.

Description

technical field [0001] The invention relates to the field of robot obstacle avoidance, in particular to a robot obstacle avoidance method based on virtual scene training. Background technique [0002] In today's Industry 4.0, all kinds of robots have entered factories, and they replace workers to complete precise, laborious, or dangerous tasks. It is obvious that the robots will not get tired, and they will strictly follow the design procedures to operate efficiently. The excellent cost-effectiveness makes robots popular in the industry. Many factories introduce robots, and by connecting appropriate sensors, the robots can interact with the environment to complete corresponding industrial tasks. [0003] However, with the popularization of industrial robots, human-machine safety issues have also been frequently raised. Although factory managers focus on human-machine safety training for workers, they attempt to control human-machine safety issues in terms of subjective ini...

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Problems solved by technology

In most cases, small changes in visual information can lead to large errors in vision-based models

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