Use pedsim_ros implementation

Author: yuxiang-gao

examples/example.py

@@ -6,19 +6,20 @@
     # initial states, each entry is the position, velocity and goal of a pedestrian: [px, py, vx, vy, gx, gy]
     initial_state = np.array(
         [
-            [0.0, 0.0, 0.5, 0.5, 10.0, 10.0],
-            [0.0, 0.5, 0.5, 0.5, 10.0, 10.0],
-            [10.0, 0.3, -0.5, 0.5, 0.0, 10.0],
-            [11.0, 0.3, -0.5, 0.5, 0.0, 10.0],
-            [12.0, 0.3, -0.5, 0.5, 0.0, 10.0],
+            # [0.0, 0.0, 0.5, 0.5, 10.0, 10.0],
+            # [0.0, 0.5, 0.5, 0.5, 10.0, 10.0],
+            [0.0, 0.0, 0.0, 0.5, 1.0, 30.0],
+            [1.0, 0.0, 0.0, 0.5, 2.0, 30.0],
+            [2.0, 0.0, 0.0, 0.5, 3.0, 30.0],
+            [3.0, 0.0, 0.0, 0.5, 4.0, 30.0],
         ]
     )
     # group informoation is represented as listes of indices of the members
-    groups = [[0, 1], [2, 3, 4]]
+    groups = [[0, 1, 2, 3]]
     # initiate the simulator,
     s = psf.Simulator(initial_state, groups=groups, obstacles=None)
     # update 80 steps
-    s.step(80)
+    s.step(150)
 
     with psf.plot.SceneVisualizer(s, "images/exmaple") as sv:
         sv.animate()

images/exmaple.gif

@@ -64,7 +64,7 @@ def make_forces(self, force_configs):
         group_forces = [
             forces.GroupCoherenceForceAlt(),
             forces.GroupRepulsiveForce(),
-            forces.GroupGazeForce(),
+            forces.GroupGazeForceAlt(),
         ]
         if self.scene_config("enable_group"):
             force_list += group_forces

pysocialforce/simulator.py

@@ -29,16 +29,16 @@ threshold = 3.0
 
 
 [group_coherence_force]
-factor = 2.0
+factor = 3.0
 
 [group_repulsive_force]
 factor = 1.0
-threshold = 0.5
+threshold = 0.8
 
 [group_gaze_force]
-factor = 5.0
+factor = 4.0
 # fov params
-fov_phi = 100.0
+fov_phi = 180.0
 
 [goal_attractive_force]
 factor = 1