Artificial Intelligence Tips
Path Planning
Path Planning is computational problem to find a sequence of valid configurations that moves the object from the source to destination. One example is the Rapidly-exploring Random Trees (RRT)
RRT
In essence, an RRT planner searches for a path froman initial state to a goal state by expanding a searchtree. First, an extend function calculates a new state that can be reached from the target state by some incremental distance. If a collision with an obstacle in the environment would occur by moving to that new state, then a default value of type state is returned to capture the fact that there is no “successor” statedue to the obstacle. In general, any heuristic methods suitable for control of the robot can be used here. The heuristic just neet to detect when a state would hit the robot, however, the better the heuristic,the fewer nodes the planner will need to expand on average. Next, the algorithm provide an estimate of the time or distance that estimates how long repeated application would take to reach the goal. Finally, returns a state drawn uniformly from the state space of the environment.
Decision Making
Decision Making (DM) is one of basic blocks of soccer robot navigation system. DM analyses the current state of the world model and makes decisions about new positions of robots, for example.