Fig 1.
Main research steps.
Fig 2.
(a) Virtual environment map cropping process. (b) Virtual environment map grid division and grayscale processing. (c) Black and white virtual environment map.
Table 1.
Obstacle information in the virtual environment map.
Fig 3.
Virtual environment grid map and coding.
(a) Obstacle box selection. (b) Binarized grid map. (c) Binarized grid map coding.
Table 2.
Grid map encoding principle.
Fig 4.
Virtual environment grid map path planning.
(a) Virtual environment grid map planning path. (b) Virtual environment grid map planning pose. (c) Virtual environment grid map planning path and virtual environment integration. (d) Virtual environment grid map planning pose and virtual environment integration.
Fig 5.
Virtual environment obstacle circular design.
(a) Virtual environment obstacle circular circle selection result. (b) Circular coverage of obstacles in the virtual environment. (c) The obstacles of the virtual environment map are circled and the map is divided into grids.
Fig 6.
Obstacle circular design map matrix and grid map.
Fig 7.
The virtual environment obstacle circular edge expansion design.
(a) The virtual environment obstacles circular edge expansion circle selection. (b) Circular edge expansion circle coverage of obstacles in the virtual environment. (c) The virtual environment obstacle circle edge expansion design grayscale image. (d) The virtual environment obstacle circle edge expansion design grid graph.
Fig 8.
Standard grid map for the expansion design of obstacle circular edges in virtual environment.
Fig 9.
Two method coding diagrams in virtual environment.
(a) Virtual environment obstacle circular design grid map coding diagram. (b) Virtual environment obstacle circular edge expansion design grid map coding diagram.
Table 3.
Parameters used for path planning of ant colony algorithm.
Fig 10.
Obstacle circular design path planning.
(a) Obstacle circular design grid map planning path. (b) Obstacle circular design grid map planning pose. (c) The integration of the grid map planning path and the virtual environment map. (d) The integration of the grid map planning pose and the virtual environment map.
Fig 11.
Obstacle circular edge expansion path planning.
(a) Obstacle circular edge expansion grid map planning path. (b) Obstacle circular edge expansion grid map planning pose. (c) The integration of the grid map planning path and the virtual environment map. (d) The integration of the grid map planning pose and the virtual environment map.
Fig 12.
Two method path planning iteration diagram in virtual environment.
(a) Virtual environment obstacle circular edge design grid map path planning iteration diagram. (b) Virtual environment obstacle circular edge expansion design grid map path planning iteration diagram.
Fig 13.
(a) Real environment map cropping process. (b) Black and white real environment map. (c) Real environment map grid graph.
Table 4.
Obstacle information in the real environment map.
Fig 14.
Real environment grid map.
Fig 15.
Real environment obstacle circular design.
(a) Real environment obstacle circular circle selection result. (b) Circular coverage of obstacles in the real environment. (c) Real environment obstacle circular design map gridding.
Fig 16.
Real environment obstacle circular design grid map.
Fig 17.
Real environment obstacle circular edge expansion design.
(a) Real environment obstacles circular edge expansion selection result. (b) Real environment obstacles circular edge expansion coverage. (c) Real environment obstacle circular edge expansion map gridding.
Fig 18.
Standard grid map for the expansion design of obstacle circular edges in real environment.
Fig 19.
Real environment grid map coding.
(a) Real environment original grid map encoding. (b) Real environment obstacle circular design grid map encoding. (c) Real environment obstacle circular edge expansion design grid map encoding. (d) Real environment map encoding.
Fig 20.
Real environment three grid maps path planning.
(a) Real environment grid map planning path, pose, and real environment map display results. (b) Circular design of real environment obstacles grid map planning path, pose, and real environment map display results. (c) Real environment obstacle circular edge expansion design grid map planning path, pose, real environment map display results.
Table 5.
Real environment three maps path planning time decomposition.
Table 6.
Real environment three maps planning time decomposition mean and standard deviation.
Fig 21.
Real environment planning path security.
(a) Real environment grid map planning path security. (b) Circular design of real environment obstacles grid map planning path security. (c) Real environment obstacle circular edge expansion design grid map planning path security.
Fig 22.
Real environment robot motion control experiments.
(a) Real environment grid map planning path motion control experiment actual trajectory, x direction error, y direction error. (b) Experiment actual trajectory, x direction error, y direction error of the real environment obstacle circular design grid map planning path motion control experiment. (c) Experiment actual trajectory, x direction error, y direction error of the real environment obstacle circular edge expansion design grid map planning path motion control experiment. (d) Coding graphs under three types of maps. (e) Experiment robot.
Fig 23.
(a)The encoding value corresponding to the pose. (b)The pose in the local grid map. (c)The pose in the local real environment map.
Fig 24.
Real environment three maps planning path security comparison.
(a) Three kinds of map path planning iteration diagrams. (b)Changes of planning path length under the three maps. (c)Safety degree change graph.
Table 7.
Experimental results of motion control in different environments.
Fig 25.
Different environments grid map planning path, real environment path, and real experiment trajectory.
(a) Experiment 1. (b)Experiment 2. (c)Experiment 3. (d)Experiment 4.
Table 8.
Experimental results of motion control under different algorithms in real environments.
Fig 26.
Display of planning paths under different algorithms in real environments.
(a) Dijkstra algorithm. (b) PRM algorithm. (c) RRTalgorithm. (d) A* algorithm. (e) APF algorithm. (f) GA algorithm.
Fig 27.
Display of planning paths in different environments.
(a) Environment 1. (b) Environment 2. (c) Environment 3. (d) Environment 4. (e) Environment 5. (f) Environment 6. (j) Environment 7. (h) Environment 8. (i) Environment 9.