GSSfearless / Path-planning-on-multiple-intelligent-agents-scenario

We optimize SIEP algorithm in multiple intelligent agents scenario and comparatively research A*, DFS, BFS, Dijkstra, PFP and PRM.

Path planning on multiple intelligent agents scenario

1. Install numpy

2. Install matplotlib

Stimuli concerned concept was inspired by Prof.ChaoYu Chen

The following is SIEP.py trajectory result, the BLUE line means short distance movement, RED line represents long distance movement, GREEN line means where robot cannot pass.

The application scenarios of experiment 2 and experiment 3 are complex terrain.

Experiment 2 result--Stimuli control

Experiment 3 result--Stimuli control

Experiment 4 is to test the performance of the SIEP algorithm in a narrow channel.The following result represents SIEP have LOCAL MINIMUM TRAP PROBLEM, and the robot can't achieve the destination.

Experiment 4 result--Stimuli control.

However, if we up-regulation the maximum velocity Vmax, the robot can achieve the destination.

DFS, BFS, Dijkstra, A*, PFP, PRM are very famous path planning algorithms.

If you have any question, please email me: [e-mail]