WIP: plot based simulation

master
mcarfagno 2020-01-13 12:25:26 +00:00
parent 60f028e25b
commit 13935940b4
11 changed files with 115 additions and 404 deletions

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cmake_minimum_required(VERSION 2.8.3)
project(husky_mpc)
## Compile as C++11, supported in ROS Kinetic and newer
# add_compile_options(-std=c++11)
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## if COMPONENTS list like find_package(catkin REQUIRED COMPONENTS xyz)
## is used, also find other catkin packages
find_package(catkin REQUIRED COMPONENTS
geometry_msgs
nav_msgs
roscpp
rospy
std_msgs
)
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# find_package(Boost REQUIRED COMPONENTS system)
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################################################
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################################################
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# DEPENDENCIES
# geometry_msgs# navigation_msgs# std_msgs
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################################################
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################################################
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## package, follow these steps:
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# cfg/DynReconf1.cfg
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# )
###################################
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###################################
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## LIBRARIES: libraries you create in this project that dependent projects also need
## CATKIN_DEPENDS: catkin_packages dependent projects also need
## DEPENDS: system dependencies of this project that dependent projects also need
catkin_package(
# INCLUDE_DIRS include
# LIBRARIES husky_mpc
# CATKIN_DEPENDS geometry_msgs navigation_msgs roscpp rospy std_msgs
# DEPENDS system_lib
)
###########
## Build ##
###########
## Specify additional locations of header files
## Your package locations should be listed before other locations
include_directories(
# include
${catkin_INCLUDE_DIRS}
)
## Declare a C++ library
# add_library(${PROJECT_NAME}
# src/${PROJECT_NAME}/husky_mpc.cpp
# )
## Add cmake target dependencies of the library
## as an example, code may need to be generated before libraries
## either from message generation or dynamic reconfigure
# add_dependencies(${PROJECT_NAME} ${${PROJECT_NAME}_EXPORTED_TARGETS} ${catkin_EXPORTED_TARGETS})
## Declare a C++ executable
## With catkin_make all packages are built within a single CMake context
## The recommended prefix ensures that target names across packages don't collide
# add_executable(${PROJECT_NAME}_node src/husky_mpc_node.cpp)
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## target back to the shorter version for ease of user use
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# set_target_properties(${PROJECT_NAME}_node PROPERTIES OUTPUT_NAME node PREFIX "")
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## same as for the library above
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# ${catkin_LIBRARIES}
# )
#############
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#############
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#############
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#############
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# if(TARGET ${PROJECT_NAME}-test)
# target_link_libraries(${PROJECT_NAME}-test ${PROJECT_NAME})
# endif()
## Add folders to be run by python nosetests
# catkin_add_nosetests(test)

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<?xml version="1.0"?>
<package format="2">
<name>husky_mpc</name>
<version>0.0.0</version>
<description>The husky_mpc package</description>
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<maintainer email="marcello@todo.todo">marcello</maintainer>
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<build_depend>geometry_msgs</build_depend>
<build_depend>nav_msgs</build_depend>
<build_depend>roscpp</build_depend>
<build_depend>rospy</build_depend>
<build_depend>std_msgs</build_depend>
<build_export_depend>geometry_msgs</build_export_depend>
<build_export_depend>nav_msgs</build_export_depend>
<build_export_depend>roscpp</build_export_depend>
<build_export_depend>rospy</build_export_depend>
<build_export_depend>std_msgs</build_export_depend>
<exec_depend>geometry_msgs</exec_depend>
<exec_depend>nav_msgs</exec_depend>
<exec_depend>roscpp</exec_depend>
<exec_depend>rospy</exec_depend>
<exec_depend>std_msgs</exec_depend>
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<export>
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</export>
</package>

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#! /usr/bin/env python
import rospy
import numpy as np
from nav_msgs.msg import Odometry
from geometry_msgs.msg import Twist
from utils import compute_path_from_wp
from cvxpy_mpc import optimize
# classes
class Node():
def __init__(self):
rospy.init_node('mpc_node')
N = 5 #number of state variables
M = 2 #number of control variables
T = 20 #Prediction Horizon
dt = 0.25 #discretization step
# State for the robot mathematical model
self.state = None
# starting guess output
self.opt_u = np.zeros((M,T))
self.opt_u[0,:] = 1 #m/s
self.opt_u[1,:] = np.radians(0) #rad/s
# Interpolated Path to follow given waypoints
self.path = compute_path_from_wp([0,20,30,30],[0,0,10,20])
self._cmd_pub = rospy.Publisher(rospy.get_namespace() + 'husky_velocity_controller/cmd_vel', Twist, queue_size=10)
self._odom_sub = rospy.Subscriber(rospy.get_namespace() +'husky_velocity_controller/odom', Odometry, self._odom_cb, queue_size=1)
def run(self):
while 1:
if self.state is not None:
#optimization loop
self.opt_u = optimize(self.state,
self.opt_u,
self.path)
msg = Twist()
msg.linear.x=self.opt_u[0,1]
msg.angular.z=self.opt_u[0,1]
self._cmd_pub(msg)
def _odom_cb(self,odom):
'''
Updates state with latest odometry.
:param odom: nav_msgs.msg.Odometry
'''
state = np.zeros(3)
# Update current position
state[0] = odom.pose.pose.position.x
state[1] = odom.pose.pose.position.y
# Update current orientation
_, _, state[2] = euler_from_quaternion(
[odom.pose.pose.orientation.x,
odom.pose.pose.orientation.y,
odom.pose.pose.orientation.z,
odom.pose.pose.orientation.w])
self.state = state
def main():
ros_node=Node()
try:
ros_node.run()
except rospy.exceptions.ROSException as e:
sys.exit(e)
if __name__ == '__main__':
main()

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@ -84,7 +84,7 @@ def calc_err(state,path):
return target_idx,psi,cte return target_idx,psi,cte
def optimize(starting_state,u_bar,track); def optimize(starting_state,u_bar,track):
''' '''
:param starting_state: :param starting_state:
:param u_bar: :param u_bar:
@ -160,7 +160,7 @@ def optimize(starting_state,u_bar,track);
constr += [x[:,t+1] == A*x[:,t] + B*u[:,t] + C.flatten()] constr += [x[:,t+1] == A*x[:,t] + B*u[:,t] + C.flatten()]
# sums problem objectives and concatenates constraints. # sums problem objectives and concatenates constraints.
constr += [x[:,0] == x_sim[:,sim_time]] # starting condition constr += [x[:,0] == x0] # starting condition
constr += [u[0, :] <= MAX_SPEED] constr += [u[0, :] <= MAX_SPEED]
constr += [u[0, :] >= MIN_SPEED] constr += [u[0, :] >= MIN_SPEED]
constr += [cp.abs(u[1, :]) <= MAX_STEER_SPEED] constr += [cp.abs(u[1, :]) <= MAX_STEER_SPEED]

91
mpc_demo/main.py Executable file
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@ -0,0 +1,91 @@
#! /usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import animation
from utils import compute_path_from_wp
from cvxpy_mpc import optimize
import sys
import time
# classes
class MPC():
def __init__(self):
# State for the robot mathematical model [x,y,heading]
self.state = np.zeros(3)
# Sim step
self.dt = 0.25
# starting guess output
N = 5 #number of state variables
M = 2 #number of control variables
T = 20 #Prediction Horizon
self.opt_u = np.zeros((M,T))
self.opt_u[0,:] = 1 #m/s
self.opt_u[1,:] = np.radians(0) #rad/s
# Interpolated Path to follow given waypoints
self.path = compute_path_from_wp([0,20,30,30],[0,0,10,20])
#Initialise plot
# First set up the figure, the axis, and the plot element we want to animate
plt.style.use("ggplot")
self.fig = plt.figure()
plt.ion()
plt.show()
def run(self):
'''
'''
while 1:
if self.state is not None:
#optimization loop
start=time.time()
self.opt_u = optimize(self.state,
self.opt_u,
self.path)
print("CVXPY Optimization Time: {:.4f}s".format(time.time()-start))
self.update_sim(self.opt_u[0,1],self.opt_u[1,1])
self.plot_sim()
def update_sim(self,lin_v,ang_v):
'''
Updates state.
:param lin_v: float
:param ang_v: float
'''
self.state[0] = self.state[0] +lin_v*np.cos(self.state[2])*self.dt
self.state[1] = self.state[1] +lin_v*np.sin(self.state[2])*self.dt
self.state[2] = self.state[2] +ang_v*self.dt
def plot_sim(self):
plt.clf()
self.ax = plt.axes(xlim=(np.min(self.path[0,:])-1, np.max(self.path[0,:])+1),
ylim=(np.min(self.path[1,:])-1, np.max(self.path[1,:])+1))
self.track, = self.ax.plot(self.path[0,:],self.path[1,:], "g-", label="reference track")
self.vehicle, = self.ax.plot([self.state[0]], [self.state[1]], "r*", label="vehicle path")
plt.legend()
plt.draw()
plt.pause(0.1)
def do_sim():
sim=MPC()
try:
sim.run()
except Exception as e:
sys.exit(e)
if __name__ == '__main__':
do_sim()

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@ -1,7 +1,5 @@
import numpy as np import numpy as np
from scipy.integrate import odeint
from scipy.interpolate import interp1d from scipy.interpolate import interp1d
import cvxpy as cp
def compute_path_from_wp(start_xp, start_yp, step = 0.1): def compute_path_from_wp(start_xp, start_yp, step = 0.1):
""" """
@ -31,3 +29,5 @@ def compute_path_from_wp(start_xp, start_yp, step = 0.1):
dx = np.append(0, np.diff(final_xp)) dx = np.append(0, np.diff(final_xp))
dy = np.append(0, np.diff(final_yp)) dy = np.append(0, np.diff(final_yp))
theta = np.arctan2(dy, dx) theta = np.arctan2(dy, dx)
return np.vstack((final_xp,final_yp,theta))

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@ -1158,13 +1158,6 @@
"plt.tight_layout()\n", "plt.tight_layout()\n",
"plt.show()" "plt.show()"
] ]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
} }
], ],
"metadata": { "metadata": {

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@ -1158,13 +1158,6 @@
"plt.tight_layout()\n", "plt.tight_layout()\n",
"plt.show()" "plt.show()"
] ]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
} }
], ],
"metadata": { "metadata": {