potential_field first commit

Author: Krithik1

local_pathfinding/planners/potential_field.py

@@ -0,0 +1,100 @@
+#!/usr/bin/env python
+
+from ompl import base as ob
+from ompl import geometric as og
+
+
+class PotentialFieldPlanner(ob.Planner):
+    """Potential Field Planner class."""
+
+    def __init__(self, si):
+        """Initialize the Potential Field Planner class.
+
+        Args:
+            si (ob.SpaceInformation): OMPL Space Information object.
+        """
+        super(PotentialFieldPlanner, self).__init(si, "PotentialFieldPlanner")
+        self.states_ = []
+
+    def solve(self, ptc) -> ob.PlannerStatus:
+        """Solve the potential field problem.
+
+        Args:
+            ptc (ob.PlannerTerminationCondition): Planner termination condition.
+
+        Returns:
+            ob.PlannerStatus: Planner status.
+        """
+        # Get the problem definition and space information
+        pdef = self.getProblemDefinition()
+        si = self.getSpaceInformation()
+        goal = pdef.getGoal()
+
+        # Get the initial and goal states
+        start = pdef.getStartState(0)
+        goal_state = goal.getState()
+
+        current_state = start
+
+        # Iterate and navigate the sailboat using the potential field
+        while not ptc():
+            # Calculate the gradient of the potential field at the current state
+            gradient = calculate_gradient(current_state, goal_state)
+
+            # Update the sailboat's position and heading based on the gradient
+            current_state = navigate_sailboat(current_state, gradient)
+
+            # Add the current state to the list of states
+            self.states_.append(current_state)
+
+            # Check if the sailboat has reached the goal
+            if si.distance(current_state, goal_state) < si.getGoal().getThreshold():
+                break
+
+        # Create a path from the list of states
+        path = og.PathGeometric(si)
+        for state in self.states_:
+            path.append(state)
+
+        # Add the path to the problem definition
+        pdef.addSolutionPath(path)
+
+        # Return the planner status
+        return ob.PlannerStatus(pdef.hasSolution(), False)
+
+    def clear(self):
+        """Clear the potential field planner."""
+        super(PotentialFieldPlanner, self).clear()
+        self.states_ = []
+
+
+def calculate_gradient(current_state, goal_state) -> tuple:
+    """Calculate the gradient of the potential field at the current state.
+
+    Args:
+        current_state (ob.State): Current state.
+        goal_state (ob.State): Goal state.
+
+    Returns:
+        tuple: Gradient vector as a tuple of floats.
+    """
+    # Calculate the gradient of the potential field at the current state
+    # This function should return the gradient vector as a tuple of floats
+
+    # Replace this with your implementation
+    return (0.0, 0.0)
+
+
+def navigate_sailboat(current_state, gradient) -> ob.State:
+    """Update the sailboat's position and heading based on the gradient.
+
+    Args:
+        current_state (ob.State): Current state.
+        gradient (tuple): Gradient vector as a tuple of floats.
+    """
+    # Update the sailboat's position and heading based on the gradient
+    # This function should adjust the boat's sail configuration and heading
+    # to align with the gradient direction
+
+    # Replace this with your implementation
+    return current_state