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motion.py
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############################################################################
# CoderBot, a didactical programmable robot.
# Copyright (C) 2014, 2015 Roberto Previtera <[email protected]>
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
#
# This program 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 General Public License for more details.
#
# You should have received a copy of the GNU General Public License along
# with this program; if not, write to the Free Software Foundation, Inc.,
# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
############################################################################
from time import time
import logging
import numpy as np
import cv2
from cv import image
from coderbot import CoderBot
from camera import Camera
from config import Config
lk_params = dict(winSize=(15, 15),
maxLevel=2,
criteria=(cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 0.03))
feature_params = dict(maxCorners=500,
qualityLevel=0.3,
minDistance=7,
blockSize=7)
PI_CAM_FOV_H_DEG = 53.0
PI_CAM_FOV_V_CM = 100.0
class Motion:
# pylint: disable=too-many-instance-attributes
def __init__(self):
self.bot = CoderBot.get_instance()
self.cam = Camera.get_instance()
self.track_len = 2
self.detect_interval = 5
self.tracks = []
self.frame_idx = 0
self.ts = time()
self.frame_gray = None
self.prev_gray = None
self.running = False
self.delta_power = 0.0
self.delta_dist = 0.0
self.target_dist = 0.0
self.delta_angle = 0.0
self.target_angle = 0.0
cfg = Config.get()
self.power_angles = [[15, (int(cfg.get("move_power_angle_1")), -1)],
[4, (int(cfg.get("move_power_angle_2")), 0.05)],
[1, (int(cfg.get("move_power_angle_3")), 0.02)],
[0, (0, 0)]]
self.image_width = 640 / int(cfg.get("cv_image_factor"))
self.image_heigth = 480 / int(cfg.get("cv_image_factor"))
self.transform = image.Image.get_transform(self.image_width)
_motion = None
@classmethod
def get_instance(cls):
if not cls._motion:
cls._motion = Motion()
return cls._motion
def move(self, dist):
self.delta_dist = 0.0
self.delta_angle = 0.0
self.target_dist = dist
self.target_angle = 0.0
self.delta_power = 0.0
self.loop_move()
def turn(self, angle):
self.delta_dist = 0.0
self.delta_angle = 0.0
self.target_dist = 0.0
self.target_angle = angle
self.loop_turn()
def stop(self):
self.running = False
def loop_move(self):
self.running = True
while self.running:
frame = self.cam.get_image()
self.frame_gray = frame.grayscale()
if len(self.tracks) < 2 or self.frame_idx % self.detect_interval == 0:
self.find_keypoints(self.frame_gray, self.tracks)
if self.tracks and self.prev_gray is not None:
self.track_keypoints(self.prev_gray, self.frame_gray, self.tracks)
if self.tracks:
delta_angle, delta_dist = self.calc_motion()
self.running = self.running and self.bot_move(self.target_dist, delta_dist, delta_angle)
self.frame_idx += 1
self.prev_gray = self.frame_gray
self.bot.stop()
def loop_turn(self):
self.running = True
while self.running:
frame = self.cam.get_image()
self.frame_gray = frame.grayscale()
if len(self.tracks) < 2 or self.frame_idx % self.detect_interval == 0:
self.find_keypoints(self.frame_gray, self.tracks)
if self.tracks and self.prev_gray is not None:
self.track_keypoints(self.prev_gray, self.frame_gray, self.tracks)
if self.tracks:
delta_angle, delta_dist = self.calc_motion()
self.running = self.running and self.bot_turn(self.target_angle, delta_angle)
self.frame_idx += 1
self.prev_gray = self.frame_gray
self.bot.stop()
def find_keypoints(self, image_gray, tracks):
#print "find_keypoints"
ts = time()
mask = np.zeros_like(image_gray._data)
mask[:] = 255
#for x, y in [np.int32(tr[-1]) for tr in tracks]:
# cv2.circle(mask, (x, y), 5, 0, -1)
p = cv2.goodFeaturesToTrack(image_gray._data, mask=mask, **feature_params)
if p is not None:
for x, y in np.float32(p).reshape(-1, 2):
tracks.append([(x, y)])
#print "fk: ", str(time() - ts)
def track_keypoints(self, prev_image, cur_image, tracks):
#print "track_keypoints"
#ts = time()
img0, img1 = prev_image._data, cur_image._data
p0 = np.float32([tr[-1] for tr in tracks]).reshape(-1, 1, 2)
p1, st, err = cv2.calcOpticalFlowPyrLK(img0, img1, p0, None, **lk_params)
p0r, st, err = cv2.calcOpticalFlowPyrLK(img1, img0, p1, None, **lk_params)
d = abs(p0-p0r).reshape(-1, 2).max(-1)
good = d < 1
#good = st
#print "tk: ", str(time() - ts)
new_tracks = []
for tr, (x, y), good_flag in zip(tracks, p1.reshape(-1, 2), good):
if not good_flag:
continue
tr.append((x, y))
if len(tr) > self.track_len:
del tr[0]
new_tracks.append(tr)
#cv2.circle(self.vis, (x, y), 2, (0, 255, 0), -1)
#print "initial tp: ", len(self.tracks), " current tp: ", len(new_tracks)
#print len(new_tracks), len(tracks)
tracks[:] = new_tracks[:]
if tracks is False:
logging.warning("lost ALL tp!")
self.bot.stop()
#exit(0)
#cv2.polylines(self.vis, [np.int32(tr) for tr in self.tracks], False, (0, 255, 0))
def calc_motion(self):
vectors = self.tracks
avg_delta_x = 0.0
avg_delta_y = 0.0
count = 0
vectors_t = []
for vect in vectors:
if len(vect) > 1:
count += 1
vectors_t.append(vect[-2])
vectors_t.append(vect[-1])
avg_delta_x += (vect[-1][0] - vect[-2][0])
vectors_t = vectors_t[:min(len(vectors_t), 20)] #max 10 keypoints
#avg_delta_x_t = 0.0
if vectors_t:
vectors_t = image.Image.transform(vectors_t, self.transform)
for v in vectors_t.reshape(-1, 2, 2):
avg_delta_y += (v[1][1] - v[0][1])
#avg_delta_x_t += v[1][0] - v[0][0]
#avg_delta_x_t = avg_delta_x_t / (vectors_t.shape[0] / 2)
#for v in vectors_t.reshape(-1, 2, 2):
#if abs(v[1][0] - v[0][0] - avg_delta_x_t) > 2:
#print "this is an obstacle: ", str(v[1]), " delta_x: ", v[1][0] - v[0][0]
if count > 0:
avg_delta_x = (avg_delta_x / count)
avg_delta_y = (avg_delta_y / (vectors_t.shape[0] / 2))
self.delta_angle -= (avg_delta_x * PI_CAM_FOV_H_DEG) / self.image_width
self.delta_dist += (avg_delta_y * PI_CAM_FOV_V_CM) / self.image_heigth
#print "count: ", count, "delta_a: ", self.delta_angle, " avg_delta_x: ", avg_delta_x, " delta_y: ", self.delta_dist, " avg_delta_y: ", avg_delta_y
#cv2.line(self.vis, (int(80+deltaAngle),20), (80,20), (0, 0, 255))
#cv2.putText(self.vis, "delta: " + str(int((self.deltaAngle*53.0)/160.0)) + " avg_delta: " + str(int(((avg_delta_x*53.0)/160.0))),
#(0,20), cv2.FONT_HERSHEY_SIMPLEX, 0.3, (0, 0, 255))
return self.delta_angle, self.delta_dist
def bot_turn(self, target_angle, delta_angle):
run = True
sign = (target_angle - delta_angle) / abs(target_angle - delta_angle)
logging.info("abs delta: %s sign delta: %s", str(abs(target_angle - delta_angle)), str(sign))
for p_a in self.power_angles:
if abs(target_angle - delta_angle) > p_a[0] and self.running:
#print "pow: ", p_a[1][0], " duration: ", p_a[1][1]
self.bot.motor_control(sign * p_a[1][0], -1 * sign * p_a[1][0], p_a[1][1])
run = p_a[1][0] > 0 #stopped
break
return run
def bot_move(self, target_dist, delta_dist, delta_angle):
base_power = 100 * (target_dist/abs(target_dist))
self.delta_power += (delta_angle * 0.01)
logging.info("base power: %s delta power: %s delta_dist: %s target_dist: %s", str(base_power), str(self.delta_power), str(delta_dist), str(target_dist))
if abs(delta_dist) < abs(target_dist):
self.bot.motor_control(min(max(base_power - self.delta_power, -100), 100), min(max(base_power + self.delta_power, -100), 100), -1)
else:
self.bot.stop()
return abs(delta_dist) < abs(target_dist)