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PRM.m
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PRM.m
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%PRM Probabilistic RoadMap navigation class
%
% A concrete subclass of the abstract Navigation class that implements the
% probabilistic roadmap navigation algorithm over an occupancy grid. This
% performs goal independent planning of roadmaps, and at the query stage
% finds paths between specific start and goal points.
%
% Methods::
% PRM Constructor
% plan Compute the roadmap
% query Find a path
% plot Display the obstacle map
% display Display the parameters in human readable form
% char Convert to string
%
% Example::
% load map1 % load map
% goal = [50,30]; % goal point
% start = [20, 10]; % start point
% prm = PRM(map); % create navigation object
% prm.plan() % create roadmaps
% prm.query(start, goal) % animate path from this start location
%
% References::
%
% - Probabilistic roadmaps for path planning in high dimensional configuration spaces,
% L. Kavraki, P. Svestka, J. Latombe, and M. Overmars,
% IEEE Transactions on Robotics and Automation, vol. 12, pp. 566-580, Aug 1996.
% - Robotics, Vision & Control, Section 5.2.4,
% P. Corke, Springer 2011.
%
% See also Navigation, DXform, Dstar, PGraph.
% Copyright (C) 1993-2017, by Peter I. Corke
%
% This file is part of The Robotics Toolbox for MATLAB (RTB).
%
% RTB is free software: you can redistribute it and/or modify
% it under the terms of the GNU Lesser General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your option) any later version.
%
% RTB is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
% GNU Lesser General Public License for more details.
%
% You should have received a copy of the GNU Leser General Public License
% along with RTB. If not, see <http://www.gnu.org/licenses/>.
%
% http://www.petercorke.com
% Peter Corke 8/2009.
classdef PRM < Navigation
properties
npoints % number of sample points
npoints0
distthresh % distance threshold, links between vertices
% must be less than this.
distthresh0 % distance threshold set by constructor option
graph % graph Object representing random nodes
vgoal % index of vertex closest to goal
vstart % index of vertex closest to start
localGoal % next vertex on the roadmap
localPath % set of points along path to next vertex
vpath % list of vertices between start and goal
gpath
end
methods
% constructor
function prm = PRM(varargin)
%PRM.PRM Create a PRM navigation object
%
% P = PRM(MAP, options) is a probabilistic roadmap navigation
% object, and MAP is an occupancy grid, a representation of a
% planar world as a matrix whose elements are 0 (free space) or 1
% (occupied).
%
% Options::
% 'npoints',N Number of sample points (default 100)
% 'distthresh',D Distance threshold, edges only connect vertices closer
% than D (default 0.3 max(size(occgrid)))
%
% Other options are supported by the Navigation superclass.
%
% See also Navigation.Navigation.
% invoke the superclass constructor, it handles some options
prm = prm@Navigation(varargin{:});
% create an empty 2D graph
prm.graph = PGraph(2);
% parse out PRM specific options and save in the navigation object
opt.npoints = 100;
opt.distthresh = 0.3*max(size(prm.occgridnav));
[opt,args] = tb_optparse(opt, varargin);
prm.npoints0 = opt.npoints;
prm.distthresh0 = opt.distthresh;
end
function plan(prm, varargin)
%PRM.plan Create a probabilistic roadmap
%
% P.plan(OPTIONS) creates the probabilistic roadmap by randomly
% sampling the free space in the map and building a graph with
% edges connecting close points. The resulting graph is kept
% within the object.
%
% Options::
% 'npoints',N Number of sample points (default is set by constructor)
% 'distthresh',D Distance threshold, edges only connect vertices closer
% than D (default set by constructor)
% 'movie',M make a movie of the PRM planning
% build a graph over the free space
prm.message('create the graph');
opt.npoints = prm.npoints0;
opt.distthresh = prm.distthresh0; % default is constructor value
opt.animate = false;
opt.movie = [];
opt = tb_optparse(opt, varargin);
prm.npoints = opt.npoints;
prm.distthresh = opt.distthresh; % actual value used is constructor value overridden here
prm.graph.clear(); % empty the graph
prm.vpath = [];
create_roadmap(prm, opt); % build the graph
end
function pp = query(prm, start, goal)
%PRM.query Find a path between two points
%
% P.query(START, GOAL) finds a path (Mx2) from START to GOAL.
%
if prm.graph.n == 0
error('RTB:PRM:noplan', 'query: no plan: run the planner');
end
checkquery(prm, start, goal)
% find the vertex closest to the goal
prm.vgoal = prm.closest(prm.goal);
if isempty(prm.vgoal)
error('RTB:PRM:nopath', 'plan: no path roadmap -> goal: rerun the planner');
end
% find the vertex closest to the start
prm.vstart = prm.closest(prm.start);
if isempty(prm.vstart)
error('RTB:PRM:nopath', 'plan: no path start -> roadmap: rerun the planner');
end
% find a path through the graph
prm.vpath = prm.graph.Astar(prm.vstart, prm.vgoal);
% the path is a list of nodes from vstart to vgoal
% discard the first vertex, since we plan a local path to it
prm.gpath = prm.vpath;
prm.gpath = prm.gpath(2:end);
if nargout > 0
pp = [prm.start prm.graph.coord(prm.vpath) prm.goal]';
end
end
function c = closest(prm, vertex, vcomponent)
% find a node close to v that is:
% - closest
% - in the same component
% - free straight line path
if nargin > 2
component = prm.graph.component(vcomponent);
end
[d,v] = prm.graph.distances(vertex);
c = [];
% test neighbours in order of increasing distance and check for a clear
% path
for i=1:length(d)
if nargin > 2
if prm.graph.component(v(i)) ~= component
continue; % not connected
end
end
if ~prm.testpath(vertex, prm.graph.coord(v(i)))
continue; % no path
end
c = v(i);
break
end
end
% Handler invoked by Navigation.path() to start the navigation process
%
% - find a path through the graph
% - determine vertices closest to start and goal
% - find path to first vertex
% Invoked for each step on the path by path() method.
function n = next(prm, p)
if all(p(:) == prm.goal)
n = []; % signal that we've arrived
return;
end
% we take the next point from the localPath
if numrows(prm.localPath) == 0
% local path is consumed, move to next vertex
if isempty(prm.gpath)
% we have arrived at the goal vertex
% make the path from this vertex to the goal coordinate
prm.localPath = bresenham(p, prm.goal);
prm.localPath = prm.localPath(2:end,:);
prm.localGoal = [];
else
% set local goal to next vertex in gpath and remove it from the list
prm.localGoal = prm.gpath(1);
prm.gpath = prm.gpath(2:end);
% compute local path to the next vertex
prm.localPath = bresenham(p, prm.graph.coord(prm.localGoal));
prm.localPath = prm.localPath(2:end,:);
prm.graph.highlight_node(prm.localGoal);
end
end
n = prm.localPath(1,:)'; % take the first point
prm.localPath = prm.localPath(2:end,:); % and remove from the path
end
function s = char(prm)
%PRM.char Convert to string
%
% P.char() is a string representing the state of the PRM
% object in human-readable form.
%
% See also PRM.display.
% invoke the superclass char() method
s = char@Navigation(prm);
% add PRM specific stuff information
s = char(s, sprintf(' graph size: %d', prm.npoints));
s = char(s, sprintf(' dist thresh: %g', prm.distthresh));
s = char(s, char(prm.graph) );
end
function plot(prm, varargin)
%PRM.plot Visualize navigation environment
%
% P.plot() displays the roadmap and the occupancy grid.
%
% Options::
% 'goal' Superimpose the goal position if set
% 'nooverlay' Don't overlay the PRM graph
%
% Notes::
% - If a query has been made then the path will be shown.
% - Goal and start locations are kept within the object.
opt.overlay = true;
opt.nodes = true;
[opt,args] = tb_optparse(opt, varargin);
% display the occgrid
plot@Navigation(prm, args{:});
if opt.overlay
hold on
prm.graph.plot('componentcolor');
if opt.nodes && ~isempty(prm.vpath)
prm.graph.highlight_path(prm.vpath, ...
'NodeFaceColor', 'y', ...
'NodeEdgeColor', 'k', ...
'EdgeColor', 'k', ...
'EdgeThickness', 2 ...
)
v0 = prm.vpath(1);
p0 = prm.graph.coord(v0);
plot([prm.start(1) p0(1)], [prm.start(2) p0(2)], 'Color', 'k', ...
'LineWidth', 1.5);
vf = prm.vpath(end);
pf = prm.graph.coord(vf);
plot([prm.goal(1) pf(1)], [prm.goal(2) pf(2)], 'Color', 'k', ...
'LineWidth', 1.5);
end
end
% % get the superclass to plot the path
% if nargin > 1
% plot@Navigation(prm, varargin{:});
% end
hold off
set(gcf, 'Color', [1 1 1])
end
end % method
methods (Access='protected')
% private methods
% create the roadmap
function create_roadmap(prm, opt)
a = Animate(opt.movie, 'fps', 5);
for j=1:prm.npoints
% pick a point not in obstacle
while true
x = prm.randi(numcols(prm.occgrid));
y = prm.randi(numrows(prm.occgrid));
if ~prm.isoccupied([x y])
break; % free cell
end
end
new = [x; y];
% add it to the graph
vnew = prm.graph.add_node(new);
% find the closest node already in the graph
[d,v] = prm.graph.distances(new);
% test neighbours in order of increasing distance and check for a clear
% path
for i=1:length(d)
if d(i) > prm.distthresh
continue; % it's too far
end
if ~prm.testpath(new, prm.graph.coord(v(i)))
continue; % no path
end
% add an edge from the found node to new
prm.graph.add_edge(v(i), vnew);
end
if opt.animate || ~isempty(opt.movie)
prm.plot()
if ~isempty(opt.movie)
a.add();
else
pause(1)
end
end
end
end
% test the path from p1 to p2 is entirely in free space
function c = testpath(prm, p1, p2)
p = bresenham(p1, p2);
for pp=p'
if prm.isoccupied(pp)
c = false;
return;
end
end
c = true;
end
end % private methods
end % classdef