## Task01 - Open-loop locomotion control

The main task is to implement a function that will steer the robot towards a given goal.

 Deadline 13. October 2018, 23:59 PST Points 3 Label in BRUTE Task01 Files to submit archive with Robot.py file and optionally RobotConst.py file Resources Task01 resource package

#### Assignment

In class Robot.py implement the goto(coord, phi=None) function. The purpose of the function is to navigate the robot towards the goal given by coordinates $coord = (x_{goal},y_{goal})$ with an optional final heading $\phi_{goal}$. The steering of the locomotion is achieved by the goto function by setting the differential steering command of the CPG locomotion controller $(v_{left}, v_{right})$. The function returns True when the robot is at the goal coordinates and False if it has collided with an obstacle en route.

Information about the current position $(x,y)$, orientation $\phi$ and collision state is provided by the RobotHAL interface through the self.robot object. The respective functions are

#get position of the robot as a tuple (float, float)
self.robot.get_robot_position()
#get orientation of the robot as float
self.robot.get_robot_orientation()
#get collision state of the robot as bool
self.robot.get_robot_collision()

The goto function has a following prescription

def goto(self, coord, phi=None):
"""

Parameters
----------
coord: (float, float)
coordinates of the robot goal
phi: float, optional
optional final heading of the robot

Returns
-------
bool
True if the destination has been reached, False otherwise
""" 

#### Approach

The open-loop locomotion towards a given goal can be approached either using a discrete regulator, or using a continuous function.

The discrete regulator operates as follows (pseudocode).

while not goal_reached:
if the difference between the current heading and the heading to the target is higher than ORIENTATION_THRESHOLD:
full speed turn towards the targets
else:
go straight        
On the other hand, the continuous navigation function is much more elegant and can look like e.g. (pseudocode):
while not goal_reached:
dphi = the difference between the current heading and the heading towards the target
v_left = -dphi*C_TURNING_SPEED + BASE_SPEED
v_right = dphi*C_TURNING_SPEED + BASE_SPEED
Where C_TURNING_SPEED is a constant that defines the aggression with which the robot will turn towards the desired heading and BASE_SPEED is the default speed of the robot when it is heading directly towards the target. Note, the continuous navigation function is inspired by the Braitenberg vehicle model which will be discussed during Lab02 - Exteroceptive sensing, Mapping and Reactive-based Obstacle Avoidance.

Also note, that in a physical world it is impossible to get to a precise specific coordinates, therefore it is sufficient to navigate “close enough”. The sufficient distance should be comparable in size to the actual robot. In our case, this distance is given as the navigation parameter DISTANCE_THLD = 0.1 #m defined in the RobotConst.py file.

#### Evaluation

The code can be evaluated using the following script

#!/usr/bin/env python3
# -*- coding: utf-8 -*-

import sys
import math
import numpy as np
sys.path.append('robot')

import Robot as rob

DISTANCE_THLD = 0.15 #m
ORIENTATION_THLD = math.pi/8

def check(pose_set, pose_real):
"""
Function to check that the navigation towards the goal has been successfull

Parameters
----------
pose_set: (float, float, float)
desired coordinates to reach (x,y,phi)
pose_real: (float, float, float)
real coordinates of the robot (x,y,phi)

Returns
-------
bool
True if the robot real position is in delta neighborhood of the desired position, False otherwise
"""
ret = True
(x1, y1, phi1) = pose_set
(x2, y2, phi2) = pose_real
dist = (x1 - x2)**2 + (y1-y2)**2
#check the distance to the target
if math.sqrt(dist) > DISTANCE_THLD:
ret = False
if not phi1 == None:
dphi = phi1 - phi2
dphi = (dphi + math.pi) % (2*math.pi) - math.pi
if dphi > ORIENTATION_THLD:
ret = False

return ret

if __name__=="__main__":
robot = rob.Robot()

route = [(1,1,None), (-1,1,math.pi/2), (-1,-1,None), (1,-1,None)]

#navigate
for waypoint in route:
pos_des = waypoint[0:2]
ori_des = waypoint[2]

print("Navigation point " + str(pos_des) + " " + str(ori_des))
#navigate the robot towards the target
status1 = robot.goto(pos_des,ori_des)

#get robot real position
pose_real = robot.get_pose()

#check that the robot reach the destination
status2 = check(waypoint, pose_real)

#print the result
print(status1, status2)

The expected output on obstacle.ttt map is

Connected to remote API server