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Assignment-03 #43

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b4aecc4
hello world
ZHAOHANBING1024 Mar 29, 2022
c1ed3b6
Merge branch 'main' into assignment-03
ZHAOHANBING1024 Mar 30, 2022
abda321
assignment_03
ZHAOHANBING1024 Mar 30, 2022
ad8d800
assignment_03
ZHAOHANBING1024 Mar 30, 2022
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1 change: 1 addition & 0 deletions lecture_04/assignment_03/hanbing_zhao/assignment_03.json
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[{"dtype": "compas.robots/Configuration", "value": {"joint_values": [0.0, 0.0, 0.0], "joint_types": [0, 0, 0], "joint_names": []}}, {"dtype": "compas.robots/Configuration", "value": {"joint_values": [1.5707963267948966, 0.0, 0.0], "joint_types": [0, 0, 0], "joint_names": []}}, {"dtype": "compas.robots/Configuration", "value": {"joint_values": [3.141592653589793, 0.0, 0.0], "joint_types": [0, 0, 0], "joint_names": []}}, {"dtype": "compas.robots/Configuration", "value": {"joint_values": [4.71238898038469, 0.0, 0.0], "joint_types": [0, 0, 0], "joint_names": []}}, {"dtype": "compas.robots/Configuration", "value": {"joint_values": [6.283185307179586, 0.0, 0.0], "joint_types": [0, 0, 0], "joint_names": []}}, {"dtype": "compas.robots/Configuration", "value": {"joint_values": [7.853981633974483, 0.0, 0.0], "joint_types": [0, 0, 0], "joint_names": []}}, {"dtype": "compas.robots/Configuration", "value": {"joint_values": [9.42477796076938, 0.0, 0.0], "joint_types": [0, 0, 0], "joint_names": []}}, {"dtype": "compas.robots/Configuration", "value": {"joint_values": [10.995574287564276, 0.0, 0.0], "joint_types": [0, 0, 0], "joint_names": []}}, {"dtype": "compas.robots/Configuration", "value": {"joint_values": [12.566370614359172, 0.0, 0.0], "joint_types": [0, 0, 0], "joint_names": []}}, {"dtype": "compas.robots/Configuration", "value": {"joint_values": [14.137166941154069, 0.0, 0.0], "joint_types": [0, 0, 0], "joint_names": []}}, {"dtype": "compas.robots/Configuration", "value": {"joint_values": [15.707963267948966, 0.0, 0.0], "joint_types": [0, 0, 0], "joint_names": []}}]
63 changes: 63 additions & 0 deletions lecture_04/assignment_03/hanbing_zhao/assignment_03.py
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"""Assignment 03: Using inverse kinematics
"""
import os
import compas
from compas_fab.backends import RosClient
from compas_fab.robots import Configuration

from compas.geometry import Frame
from compas.geometry import Point
from compas.geometry import Vector

import math
import json


# Step 1: Inside this function, complete the main part of the solution for the assignment:
# - Taking a robot and a list of frames as parameter, calculate a feasible configuration for each of the frames
# - Try to find an optimal start_configuration for each so that the motion from one config to the next is minimized
def calculate_ik_for_frames(robot, frames):
configs = []
start_configuration = Configuration.from_revolute_values([math.pi/2, 0., 0., 0.,0.,0.])

for i in range(len(frames)):
# config = Configuration.from_revolute_values([i * math.pi/2, 0., 0., 0.,0.,0.])
config = robot.inverse_kinematics(frames[i], start_configuration, group=None, return_full_configuration=False, options=None)
# config.joint_values
configs.append(config)
return configs


# Step 2: store all found configurations in a JSON file using compas.json_dump or compas.json_dumps
def store_configurations(configurations, filename):
compas.json_dump(configurations, filename) # not the 'filename'

# Use the following to test from the command line
# Or copy solution_viewer.ghx next to the folder where you created assignment_03.py to visualize the same in Grasshopper
if __name__ == '__main__':

frames = [
Frame(Point(-0.329, 0.059, 0.082), Vector(1.000, 0.000, 0.000), Vector(0.000, -1.000, 0.000)),
Frame(Point(-0.260, 0.129, 0.082), Vector(1.000, 0.000, 0.000), Vector(0.000, -1.000, 0.000)),
Frame(Point(-0.186, 0.194, 0.082), Vector(1.000, 0.000, 0.000), Vector(0.000, -1.000, 0.000)),
Frame(Point(-0.106, 0.252, 0.082), Vector(1.000, 0.000, 0.000), Vector(0.000, -1.000, 0.000)),
Frame(Point(-0.020, 0.299, 0.082), Vector(1.000, 0.000, 0.000), Vector(0.000, -1.000, 0.000)),
Frame(Point(0.074, 0.329, 0.082), Vector(1.000, 0.000, 0.000), Vector(0.000, -1.000, 0.000)),
Frame(Point(0.172, 0.330, 0.082), Vector(1.000, 0.000, 0.000), Vector(0.000, -1.000, 0.000)),
Frame(Point(0.263, 0.295, 0.082), Vector(1.000, 0.000, 0.000), Vector(0.000, -1.000, 0.000)),
Frame(Point(0.339, 0.233, 0.082), Vector(1.000, 0.000, 0.000), Vector(0.000, -1.000, 0.000)),
Frame(Point(0.400, 0.155, 0.082), Vector(1.000, 0.000, 0.000), Vector(0.000, -1.000, 0.000)),
Frame(Point(0.448, 0.070, 0.082), Vector(1.000, 0.000, 0.000), Vector(0.000, -1.000, 0.000))]

# Loads the robot from ROS
with RosClient('localhost') as client:
robot = client.load_robot()

# Step 1: calculate IK solutions for each frame
configurations = calculate_ik_for_frames(robot, frames)
print("Found {} configurations".format(len(configurations)))

# Step 2: store all configurations in a JSON file
filename = os.path.join(os.path.abspath(os.path.dirname(__file__)), 'assignment_03.json')
store_configurations(configurations, filename)
print("Stored results in {}".format(filename))
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