Multi-fire-fighting inspection collaborative robot system based on integral reinforcement learning

Abstract

The invention relates to a multi-fire-fighting inspection collaborative robot system based on integral reinforcement learning, and belongs to the field of robots. The system comprises a hardware layer, an interaction layer, a sensing layer and a control layer; the hardware layer adopts a DSP as a controller, data collected by a speedometer and a gyroscope are sent into the DSP to be processed, and the position of the robot in an inspection map is calculated in real time. A speed instruction is sent to the DSP through an upper computer, and the DSP encodes the obtained speed information to control the operation of a servo motor; the fire-fighting inspection robot adopts crawler-type driving; and when a mechanical arm needs to act, ros system in the upper computer passes through moveit! platform for motion trail planning of target point to which the mechanical arm is to move, discretizes the planned motion trail and then sends the discretized motion trail to the DSP, and the DSP controls the servo motor of the mechanical arm to move to reach the target point after obtaining the angular speed and the accelerated speed of each axis.

Description

technical field [0001] The invention belongs to the field of robots, and relates to a multi-fire inspection collaborative robot system based on integral reinforcement learning. Background technique [0002] At present, the main structure of the common fire inspection robot is: wheel drive is used in the drive; flame detectors and temperature sensors are installed around the robot to facilitate fire detection; the robot is equipped with a camera in front of the robot to transmit the inspection screen through the wireless module to the control room; a fixed but rotatable fire sprinkler is installed above the robot for external water pipes or small water pumps to extinguish the fire; in terms of robot control, with the development of multi-machine collaboration ideas and theories, in order to complete For the inspection of large areas, in order to improve the inspection efficiency and reduce the difficulty of inspection, multiple fire inspection robots are usually used to coope...

AI Technical Summary

Problems solved by technology

[0003] However, there are also many defects in the above-mentioned system. Firstly, the wheel drive makes the robot have poor passing performance on stairs and rough roads, and the flexibility of steering and rotation is not high enough; and the accuracy of flame detection by using flame detectors and temperature sensors and timeliness cannot be well guaranteed, and the range of flame detection is also small; secondly, after the flame is detected, it can only realize the alarm function and transmit the position of the ignition point and the image of the fire situation obtained through the camera to the fire control room , a small number of fire inspection robots can also cooperate with their own fire sprinklers to extinguish the fire point under the remote control of firefighters, but overall they lack flexibility and initiative in fire response; finally, multi-robot In terms of collaborative control, the centralized control method makes each individual robot have no ability to choose actions and coordinate with each other, which makes the inspection efficiency, robustness and scalability of the entire system poor, and each robot is patrolling. The optimal time and energy in the inspection process cannot be guaranteed, which will reduce the overall battery life and anti-disturbance ability to the outside world, and the autonomous control and intelligent level still need to be improved.

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