Motion Modeling And Trajectory Analysis Of Mine Ventilation Monitoring Robot

It is necessary to monitor the gas environment in coal mine for a long time to ensure safety in coal mine production,which requires to ensure that the ventilation monitoring robot maintains a reliable operation state with keeping a long period.Flexibility,monitoring range,and accuracy of the existing ventilation monitoring devices in the working process are limited due to that are affected by structure or working environment.Selecting more flexible equipment and discussing its motion and trajectory planning is necessary.To plan a ventilation monitoring trajectory with smooth motion and high work efficiency,this paper conducts an in-depth study on the motion and trajectory planning of the serial ventilation monitoring robot through theoretical derivation,data processing,and model simulation.Firstly,the robot kinematic model and joint trajectory planning are investigated.A standard D-H parametric model is created and robot‘s forward and reverse kinematics are analyzed.Meanwhile,the working range of the monitoring end is determined using Monte Carlo stochastic method.The robot joint trajectory is planned and a double S-shaped joint trajectory with smooth acceleration transition and controllable maximum velocity are generated by mixing different polynomial interpolation curves.Next,the underground gas environment is analyzed in the coal mine.The ventilation network diagram is drawn according to the actual ventilation system.The network diagram structure is simplified using the additive edge and Dijkstra methods to determine the key ventilation branch locations.The wind network solution equations are established based on the ventilation theory of mine air volume and pressure to provide support for the subsequent analysis.By combining a coal mine ventilation system model are established in Ventsim with the simulation result and relevant standards,the key locations for monitoring are determined.The gas model of the transport roadway is established,and the gas distribution mainly of CH₄ is simulated by Fluent to determine the distribution of monitoring points and gas detection range at the key locations.Finally,the robot path planning and movement simulation are discussed in depth.In this paper,the particle swarm algorithm is improved based on the genetic principle,and the performance of the improved particle swarm algorithm is tested by traversing 48 preset points.The improved algorithm is used to optimize the running trajectory of the ventilation monitoring robot,and its motion process is jointly simulated in Matlab and Coppeliasim,comparing the motion curves before and after planning.The simulation results show that the trajectory motion is more stable and the damage caused by vibration is reduced.This paper carried out an in-depth study on the robot’s trajectory in ventilation monitoring work,analyzed the robot’s installation position and detection range combined with the theories of coal mine wind network calculation and gas flow,and used the improved particle swarm optimization algorithm for trajectory planning to plan the machine’s trajectory with the shortest path and smooth running process in a short time.It provided reference for the trajectory planning research of the same type of special robots.