robotsorcerer

<?xml version="1.0"?>
<Node name="DomeRingNode" gravity="0 -9.81 0" dt=".02">
	<EulerImplicitSolver name="domeRing_cg_odesolver" printLog="false" />
	<CGLinearSolver iterations="25" name="linear solver_dome_ring" tolerance="1.0e-9" threshold="1.0e-9" />
	<!-- <MeshObjLoader name="dome_ring_loader"  filename="../../../../ros/srs_traj_opt/patient_description/meshes/dome/dome_ring.obj"  scale="1"/> -->
	<MeshVTKLoader name="vtkDomeRingLoader" filename="../../../../ros/srs_traj_opt/patient_description/meshes/dome/dome_ring.vtu" />
	<TetrahedronSetTopologyContainer name="TetraTopologyContainer_dome_ring" src="@vtkDomeRingLoader" />
	<MechanicalObject name="dofs" src="@vtkDomeRingLoader" template="Vec3d" showIndices='false' showIndicesScale='4e-5' rx='0' dz='0'/>
	<TetrahedronSetGeometryAlgorithms template="Vec3d" name="domeRing_TetraGeomAlgo"  drawTetrahedra="1"/>
	<TetrahedronSetTopologyAlgorithms template="Vec3d" name="domeRing_TetraTopologyAlgo" />

robotsorcerer

from __future__ import print_function

'An easy implementation of the Kalman-Bucy Filter'
'Ref: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.361.6851&rep=rep1&type=pdf'

import rospy.  # you don't have to use rospy
import numpy as np
# handle_soro_pose is a function wrapper around a ros service that retrieves sensor observations in real time.
from scripts.service_clinet import handle_soro_pose 

robotsorcerer

%% Class Kappa functions
% alpha = arctan(r) is a class kappa function
clc; close all
r = linspace(1, 1000);
alpha = atan(r);
subplot(221)
plot(alpha, 'LineWidth',3); hold on;
grid on;
xlabel('r'); ylabel('\alpha=tan^{-1}(r)')
title('Class \kappa function')

robotsorcerer

__all__ = [
            "Bundle", "ZEROS_TYPE", "ONES_TYPE", "rad2deg", "deg2rad",
            "realmin", "DEFAULT_ORDER", "mat_like_array", "index_array",
            "quickarray", "ismember", "omin", "omax", "strcmp", "isbundle", 
            "isfield", "cputime","error", "realmax", "eps", "info","warn", 
            "debug", "length","size",  "to_column_mat", "numel", "numDims", 
            "ndims", "expand", "ones", "zeros", "isvector", "isColumnLength",
            "cell",  "iscell", "isnumeric", "isfloat", "isscalar", "is_symmetric", 
            "precc", "succ", "psdpart", "kron", "check_shape",  "sys_integrator",
            "is_pos_def", "sympart", "place_varga", "place", "acker", "is_observable",

robotsorcerer

#!/usr/bin/env python3

__all__ = ["SubscribeRegress"]

import os
import sys
import time
import rospy
import logging
import pickle

robotsorcerer

from collections import namedtuple
import random
# tree policy is the prior probability of the node that won
Transition = namedtuple('Transition',
						('state', 'tree_policy', 'winner'))

class AgentMemory(object):
	def __init__(self, max_cap):
		"""