* @brief Searches k-nearest neighbors * @param query the point in the KD Tree * @param k k nearest neighbors * @return k-nearest neighbo

* @brief Generate knot vector. * @param parameters The parameters of given points * @param n The number of data points * @return knot The

* @brief linear velocity regularization * @param v_in raw linear velocity * @param v_d desired linear velocity * @return v regulated linear v

* @brief plan a path given start and goal in world map * @param start start in world map * @param goal goal in world map * @param plan plan * @r

* @brief Regeister planning service * @param req request from client * @param resp response from server * @return true */

* @brief Modify the map when collision occur between x and y in path, and then do * processState() * @param x DNode pointer of one DNode */

* @brief Searches the nearest neighbor * @param query the point in the KD Tree * @param min_dist the min distance between query and its nea

* @brief Normalizes roll_, pitch_, and yaw_ to [-PI, PI). */

Overrides base class method

The constructor must have no arguments, so we can't give the constructor the parameters it needs to fully initialize.

The constructor must have no arguments, so we can't give the constructor the parameters it needs to fully initialize.

* @brief Overloading operator != for Node class * @param n another Node * @return true if current node equals node n, else false */

* @brief Compare cost between 2 nodes * @param n1 one Node * @param n2 another Node * @return true if the cost to get to n1 is greater

* @brief Compare coordinates between 2 nodes * @param n1 one Node * @param n2 another Node * @return true if n1 equals n2, else false

* @brief Overloading operator + for Node class * @param n another Node * @return Node with current node's and input node n's values added */

* @brief Overloading operator - for Node class * @param n another Node * @return Node with current node's and input node n's values subtracted

* @brief operator== for comparisons * @param Node2D right hand side node reference * @return If cell indices are equal */

* @brief Overloading operator == for Node class * @param n another Node * @return true if current node equals node n, else false */

* @brief Ant update optimization iteration * @param ant Ants to be updated for velocity * @param best_ant Global optimal ant * @param gen

* @brief Genets update optimization iteration * @param genets_p individuals selected for retention * @param genets_c descendants of select

* @brief Particle update optimization iteration * @param particle Particles to be updated for velocity * @param best_particle Global optimal

* @brief Calculate parameters using the `uniform spaced` or `chrod length` or `centripetal` method. * @param points Path points * @return param

Set the rendering style (cylinders, meshes, ...) of tracked persons

Set the rendering style (cylinders, meshes, ...) of tracked persons

Set the rendering style (cylinders, meshes, ...) of tracked persons

Set the rendering style (cylinders, meshes, ...) of detected persons

* @brief RRT implementation * @param start start node * @param goal goal node * @param expand containing the node been search during th

* @brief RRT implementation * @param start start node * @param goal goal node * @param path The resulting path in (x, y,

* @brief RRT-Connect implementation * @param start start node * @param goal goal node * @param expand containing the node been search d

* @brief Informed RRT* implementation * @param start start node * @param goal goal node * @param expand containing the node been search

* @brief GA implementation * @param start start node * @param goal goal node * @param path The resulting path in (x, y, t

* @brief PSO implementation * @param start start node * @param goal goal node * @param path The resulting path in (x, y,

* @brief ACO implementation * @param start start node * @param goal goal node * @param path The resulting path in (x, y,

* @brief A* implementation * @param start start node * @param goal goal node * @param path The resulting path in (x, y

* @brief Theta* implementation * @param start start node * @param goal goal node * @param path The resulting path in (x,

* @brief Lazy implementation * @param start start node * @param goal goal node * @param path The resulting path in (x,

* @brief Voronoi-based planning implementation * @param start start node * @param goal goal node * @param path optimal pa

* @brief Lazy Theta* implementation * @param start start node * @param goal goal node * @param path The resulting path in

* @brief D* implementation * @param start start node * @param goal goal node * @param expand containing the node been se

* @brief D* lite implementation * @param start start node * @param goal goal node * @param expand containing the node been search during the

* @brief LPA* implementation * @param start start node * @param goal goal node * @param expand containing the node been search during the pro

* @brief S-Theta* implementation * @param start start node * @param goal goal node * @param path The resulting path in (x

* @brief Creates a path between the start and goal points while expanding nodes. * @param start The starting node in (x, y, theta). * @param goal

Implement of maps layer application.