Rescue work after a coal mine accident is fraught with challenges and dangers. Considering the safety of rescue workers and the urgency of a rescue mission, it is necessary to use coal mine rescue robots to perform the tasks of environmental detection and rescue. As a key part of the robot sensing system, a visual sensor can provide much information about a scene. Among vision sensor types, binocular vision has the advantages of being noncontact and passive, and it is the key technology for a robot to acquire obstacle information and reconstruct a three-dimensional scene. Therefore, coal mine rescue robots based on binocular vision have become a popular research topic in the field of mine safety. First, the research status of camera calibration and stereo vision matching for binocular vision is systematically introduced in this paper. Second, the latest research progress on coal mine rescue robots based on binocular vision is reviewed from the perspective of technological applications and development. Finally, the technical challenges and future development trends of binocular vision in coal mine rescue robots are described. INDEX TERMS Coal mine rescue robots, binocular vision, camera calibration, stereo vision matching.

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The autonomous positioning of tunneling equipment is the key to intellectualization and robotization of a tunneling face. In this paper, a method based on simultaneous localization and mapping (SLAM) to estimate the body pose of a roadheader and build a navigation map of a roadway is presented. In terms of pose estimation, an RGB-D camera is used to collect images, and a pose calculation model of a roadheader is established based on random sample consensus (RANSAC) and iterative closest point (ICP); constructing a pose graph optimization model with closed-loop constraints. An iterative equation based on Levenberg–Marquadt is derived-, which can achieve the optimal estimation of the body pose. In terms of mapping, LiDAR is used to experimentally construct the grid map based on open-source algorithms, such as Gmapping, Cartographer, Karto, and Hector. A point cloud map, octree map, and compound map are experimentally constructed based on the open-source library RTAB-MAP. By setting parameters, such as the expansion radius of an obstacle and the updating frequency of the map, a cost map for the navigation of a roadheader is established. Combined with algorithms, such as Dijskra and timed-elastic-band, simulation experiments show that the combination of octree map and cost map can support global path planning and local obstacle avoidance.

Acceleration sensor is usually used to test the performance of equipment under high-acceleration vibration. It is widely used in aero-engine, steam turbine and other equipment working in high-acceleration vibration environment. Calibration is an important means to ensure the accuracy and reliability of the measurement results of the acceleration sensor. Aiming at the conventional intermediate frequency (IF) calibration system using many instruments and complicated operation, this paper designs a resonant high-acceleration calibration system based resonant beam. First, the system amplifies the acceleration amplitude through the resonance of the resonant beam at the natural frequency, thereby generating high-acceleration values to calibrate the sensor. Then the vibration control algorithm of the calibration system is optimized, and the stability of the system is verified through experiments. Finally, the communication between the upper and lower computers is carried out in the vibration control system and the laser measurement system, and the metrological traceability is realized. The experimental results show that the system can effectively calibrate the sensitivity amplitude and phase of high-acceleration sensor in the frequency range of 100-2148 Hz and the acceleration range of 50-11 853 m s −2 . This calibration system is of great significance to the research on the calibration of IF acceleration sensor.