diff --git a/py-hpp-rbprm-robot-data/Makefile b/py-hpp-rbprm-robot-data/Makefile
index 34cf2c8d19486310c95fccb53540a7c10c636125..71f34e1fc0536f9f1fa84adc2c730ad9f98a5f31 100644
--- a/py-hpp-rbprm-robot-data/Makefile
+++ b/py-hpp-rbprm-robot-data/Makefile
@@ -4,7 +4,6 @@
HPP_PACKAGE= hpp-rbprm-robot-data
HPP_COMMENT= file database
-PKGREVISION= 2
CATEGORIES= wip
diff --git a/py-hpp-rbprm-robot-data/distinfo b/py-hpp-rbprm-robot-data/distinfo
index be57c62ae9bcc2fab84886de57bd66b0d0f5f403..3da234ef9c9510b08ecb65e3e35b8c87126c44de 100644
--- a/py-hpp-rbprm-robot-data/distinfo
+++ b/py-hpp-rbprm-robot-data/distinfo
@@ -1,4 +1,3 @@
-SHA1 (hpp-rbprm-robot-data-4.7.0.tar.gz) = 9234a2d94927349b35866213dd9b28e7e77f7569
-RMD160 (hpp-rbprm-robot-data-4.7.0.tar.gz) = 1c010b33843edbf6bba0d7ca77d474202638e115
-Size (hpp-rbprm-robot-data-4.7.0.tar.gz) = 21669530 bytes
-SHA1 (patch-aa) = ac70c4a98d77e3adb46d1326a0b27081ac712089
+SHA1 (hpp-rbprm-robot-data-4.8.0.tar.gz) = 4ea8d025095091ce556752f584b6b118749f529a
+RMD160 (hpp-rbprm-robot-data-4.8.0.tar.gz) = dad5cdc27727d22a5cbb04ad2186495c2cf50520
+Size (hpp-rbprm-robot-data-4.8.0.tar.gz) = 21691535 bytes
diff --git a/py-hpp-rbprm-robot-data/patches/patch-aa b/py-hpp-rbprm-robot-data/patches/patch-aa
deleted file mode 100644
index 776dd54bd420864c1ad17d6cceb23510b2363169..0000000000000000000000000000000000000000
--- a/py-hpp-rbprm-robot-data/patches/patch-aa
+++ /dev/null
@@ -1,319 +0,0 @@
-From fefc22afebdc46fb7a8677167a5c7803cbcbb0d8 Mon Sep 17 00:00:00 2001
-From: Guilhem Saurel <guilhem.saurel@laas.fr>
-Date: Sat, 5 Oct 2019 10:51:49 +0200
-Subject: [PATCH] [Python] remove tabs
-
----
- .../com_inequalities/obj_to_constraints.py | 279 +++++++++---------
- 1 file changed, 146 insertions(+), 133 deletions(-)
-
-diff --git a/data/hyq/com_inequalities/obj_to_constraints.py b/data/hyq/com_inequalities/obj_to_constraints.py
-index f7d7997..2d2091a 100644
---- data/hyq/com_inequalities/obj_to_constraints.py
-+++ data/hyq/com_inequalities/obj_to_constraints.py
-@@ -1,156 +1,169 @@
- #do the loading of the obj file
--import numpy as np
- from collections import namedtuple
-+from pickle import dump, load
-+
-+import numpy as np
-+
- ObjectData = namedtuple("ObjectData", "V T N F")
- Inequalities = namedtuple("Inequality", "A b N V")
-
-+
- def toFloat(stringArray):
-- res= np.zeros(len(stringArray))
-- for i in range(0,len(stringArray)):
-- res[i] = float(stringArray[i])
-- return res
--
--def load_obj(filename) :
-- V = [] #vertex
-- T = [] #texcoords
-- N = [] #normals
-- F = [] #face indexies
--
-- fh = open(filename)
-- for line in fh :
-- if line[0] == '#' : continue
--
-- line = line.strip().split(' ')
-- if line[0] == 'v' : #vertex
-- V.append(toFloat(line[1:]))
-- elif line[0] == 'vt' : #tex-coord
-- T.append(line[1:])
-- elif line[0] == 'vn' : #normal vector
-- N.append(toFloat(line[1:]))
-- elif line[0] == 'f' : #face
-- face = line[1:]
-- for i in range(0, len(face)) :
-- face[i] = face[i].split('/')
-- # OBJ indexies are 1 based not 0 based hence the -1
-- # convert indexies to integer
-- for j in range(0, len(face[i])):
-- if j!=1:
-- face[i][j] = int(face[i][j]) - 1
-- F.append(face)
--
-- return ObjectData(V, T, N, F)
--
--def inequality(v, n):
-- #the plan has for equation ax + by + cz = d, with a b c coordinates of the normal
-- #inequality is then ax + by +cz -d <= 0
-- # last var is v because we need it
-- return [n[0], n[1], n[2], np.array(v).dot(np.array(n))]
--
-+ res = np.zeros(len(stringArray))
-+ for i in range(0, len(stringArray)):
-+ res[i] = float(stringArray[i])
-+ return res
-+
-+
-+def load_obj(filename):
-+ V = [] #vertex
-+ T = [] #texcoords
-+ N = [] #normals
-+ F = [] #face indexies
-+
-+ fh = open(filename)
-+ for line in fh:
-+ if line[0] == '#': continue
-+
-+ line = line.strip().split(' ')
-+ if line[0] == 'v': #vertex
-+ V.append(toFloat(line[1:]))
-+ elif line[0] == 'vt': #tex-coord
-+ T.append(line[1:])
-+ elif line[0] == 'vn': #normal vector
-+ N.append(toFloat(line[1:]))
-+ elif line[0] == 'f': #face
-+ face = line[1:]
-+ for i in range(0, len(face)):
-+ face[i] = face[i].split('/')
-+ # OBJ indexies are 1 based not 0 based hence the -1
-+ # convert indexies to integer
-+ for j in range(0, len(face[i])):
-+ if j != 1:
-+ face[i][j] = int(face[i][j]) - 1
-+ F.append(face)
-+
-+ return ObjectData(V, T, N, F)
-+
-+
-+def inequality(v, n):
-+ #the plan has for equation ax + by + cz = d, with a b c coordinates of the normal
-+ #inequality is then ax + by +cz -d <= 0
-+ # last var is v because we need it
-+ return [n[0], n[1], n[2], np.array(v).dot(np.array(n))]
-+
-+
- def as_inequalities(obj):
-- #for each face, find first three points and deduce plane
-- #inequality is given by normal
-- A= np.empty([len(obj.F), 3])
-- b = np.empty(len(obj.F))
-- V = np.ones([len(obj.F), 4])
-- N = np.empty([len(obj.F), 3])
-- for f in range(0, len(obj.F)):
-- face = obj.F[f]
-- v = obj.V[face[0][0]]
-- # assume normals are in obj
-- n = obj.N[face[0][2]]
-- ineq = inequality(v,n)
-- A[f,:] = ineq[0:3]
-- b[f] = ineq[3]
-- V[f,0:3] = v
-- N[f,:] = n
-- return Inequalities(A,b, N, V)
--
-+ #for each face, find first three points and deduce plane
-+ #inequality is given by normal
-+ A = np.empty([len(obj.F), 3])
-+ b = np.empty(len(obj.F))
-+ V = np.ones([len(obj.F), 4])
-+ N = np.empty([len(obj.F), 3])
-+ for f in range(0, len(obj.F)):
-+ face = obj.F[f]
-+ v = obj.V[face[0][0]]
-+ # assume normals are in obj
-+ n = obj.N[face[0][2]]
-+ ineq = inequality(v, n)
-+ A[f, :] = ineq[0:3]
-+ b[f] = ineq[3]
-+ V[f, 0:3] = v
-+ N[f, :] = n
-+ return Inequalities(A, b, N, V)
-+
-+
- def is_inside(inequalities, pt):
-- return ((inequalities.A.dot(pt) - inequalities.b) < 0).all()
-+ return ((inequalities.A.dot(pt) - inequalities.b) < 0).all()
-+
-
- #~ def rotate_inequalities_q():
-
-+
- # TODO this is naive, should be a way to simply update d
- def rotate_inequalities(ineq, transform):
-- #for each face, find first three points and deduce plane
-- #inequality is given by normal
-- A = np.empty([len(ineq.A), 3])
-- b = np.empty(len(ineq.b))
-- V = np.ones([len(ineq.V), 4])
-- N = np.ones([len(ineq.N), 3])
-- for i in range(0, len(b)):
-- v = transform.dot(ineq.V[i,:])
-- n = transform[0:3,0:3].dot(ineq.N[i,0:3])
-- ine = inequality(v[0:3],n[0:3])
-- A[i,:] = ine[0:3]
-- b[i] = ine[3]
-- V[i,:] = v
-- N[i,:] = n
-- return Inequalities(A,b, N, V)
--
--from pickle import dump
-+ #for each face, find first three points and deduce plane
-+ #inequality is given by normal
-+ A = np.empty([len(ineq.A), 3])
-+ b = np.empty(len(ineq.b))
-+ V = np.ones([len(ineq.V), 4])
-+ N = np.ones([len(ineq.N), 3])
-+ for i in range(0, len(b)):
-+ v = transform.dot(ineq.V[i, :])
-+ n = transform[0:3, 0:3].dot(ineq.N[i, 0:3])
-+ ine = inequality(v[0:3], n[0:3])
-+ A[i, :] = ine[0:3]
-+ b[i] = ine[3]
-+ V[i, :] = v
-+ N[i, :] = n
-+ return Inequalities(A, b, N, V)
-+
-+
- def ineq_to_file(ineq, filename):
-- f1=open(filename, 'w+')
-- res = { 'A' : ineq.A, 'b' : ineq.b, 'N' : ineq.N, 'V' : ineq.V}
-- dump(res, f1)
-- f1.close()
--
--from pickle import load
-+ f1 = open(filename, 'w+')
-+ res = {'A': ineq.A, 'b': ineq.b, 'N': ineq.N, 'V': ineq.V}
-+ dump(res, f1)
-+ f1.close()
-+
-+
- def ineq_from_file(filename):
-- f1=open(filename, 'r')
-- res = load(f1)
-- return Inequalities(res['A'], res['b'],res['N'],res['V'])
--
-+ f1 = open(filename, 'r')
-+ res = load(f1)
-+ return Inequalities(res['A'], res['b'], res['N'], res['V'])
-+
-+
- def test_inequality():
-- n = np.array([0,-1,0])
-- v = np.array([0,1,1])
-- if inequality(v,n) != [0,-1,0,-1]:
-- print("error in test_inequality")
-- else:
-- print("test_inequality successful")
-+ n = np.array([0, -1, 0])
-+ v = np.array([0, 1, 1])
-+ if inequality(v, n) != [0, -1, 0, -1]:
-+ print("error in test_inequality")
-+ else:
-+ print("test_inequality successful")
-+
-
- def __gen_data():
-- obj = load_obj('./hrp2/RL_com._reduced.obj')
-- ineq = as_inequalities(obj)
-- ok_points = [[0,0,0], [0.0813, 0.0974, 0.2326], [-0.3387, 0.1271, -0.5354]]
-- not_ok_points = [[-0.3399, 0.2478, -0.722],[-0.1385,-0.4401,-0.1071]]
-- return obj, ineq, ok_points, not_ok_points
-+ obj = load_obj('./hrp2/RL_com._reduced.obj')
-+ ineq = as_inequalities(obj)
-+ ok_points = [[0, 0, 0], [0.0813, 0.0974, 0.2326], [-0.3387, 0.1271, -0.5354]]
-+ not_ok_points = [[-0.3399, 0.2478, -0.722], [-0.1385, -0.4401, -0.1071]]
-+ return obj, ineq, ok_points, not_ok_points
-+
-
- def test_belonging():
-- data = __gen_data()
-- ineq = data[1]
-- ok_points = data[2]
-- not_ok_points = data[3]
-- for p in ok_points:
-- assert (is_inside(ineq, np.array(p))), "point " + str(p) + " should be inside object"
-- for p in not_ok_points:
-- assert (not is_inside(ineq, np.array(p))), "point " + str(p) + " should NOT be inside object"
-- print("test_belonging successful")
--
-+ data = __gen_data()
-+ ineq = data[1]
-+ ok_points = data[2]
-+ not_ok_points = data[3]
-+ for p in ok_points:
-+ assert (is_inside(ineq, np.array(p))), "point " + str(p) + " should be inside object"
-+ for p in not_ok_points:
-+ assert (not is_inside(ineq, np.array(p))), "point " + str(p) + " should NOT be inside object"
-+ print("test_belonging successful")
-+
-+
- def test_rotate_inequalities():
--
-- tr = np.array([[ 1. , 0. , 0. , 0. ],
-- [ 0. , 0.98006658, -0.19866933, 2. ],
-- [ 0. , 0.19866933, 0.98006658, 0. ],
-- [ 0. , 0. , 0. , 1. ]])
--
-- data = __gen_data()
-- ineq = rotate_inequalities(data[1], tr)
-- ok_points = [tr.dot(np.array(el + [1]))[0:3] for el in data[2]]
-- not_ok_points = [tr.dot(np.array(el + [1]))[0:3] for el in data[3]]
-- for p in ok_points:
-- assert (is_inside(ineq, p)), "point " + str(p) + " should be inside object"
-- for p in not_ok_points:
-- assert (not is_inside(ineq, p)), "point " + str(p) + " should NOT be inside object"
-- print("test_rotate_inequalities successful")
--
-+
-+ tr = np.array([[1., 0., 0., 0.], [0., 0.98006658, -0.19866933, 2.], [0., 0.19866933, 0.98006658, 0.],
-+ [0., 0., 0., 1.]])
-+
-+ data = __gen_data()
-+ ineq = rotate_inequalities(data[1], tr)
-+ ok_points = [tr.dot(np.array(el + [1]))[0:3] for el in data[2]]
-+ not_ok_points = [tr.dot(np.array(el + [1]))[0:3] for el in data[3]]
-+ for p in ok_points:
-+ assert (is_inside(ineq, p)), "point " + str(p) + " should be inside object"
-+ for p in not_ok_points:
-+ assert (not is_inside(ineq, p)), "point " + str(p) + " should NOT be inside object"
-+ print("test_rotate_inequalities successful")
-+
-
- def load_obj_and_save_ineq(in_name, out_name):
-- obj = load_obj(in_name)
-- ineq = as_inequalities(obj)
-- ineq_to_file (ineq, out_name)
--
--load_obj_and_save_ineq('./lfleg_com_reduced.obj','./lfleg_com.ineq')
--load_obj_and_save_ineq('./lhleg_com_reduced.obj','./lhleg_com.ineq')
--load_obj_and_save_ineq('./rhleg_com_reduced.obj','./rhleg_com.ineq')
--load_obj_and_save_ineq('./rfleg_com_reduced.obj','./rfleg_com.ineq')
-+ obj = load_obj(in_name)
-+ ineq = as_inequalities(obj)
-+ ineq_to_file(ineq, out_name)
-+
-+
-+load_obj_and_save_ineq('./lfleg_com_reduced.obj', './lfleg_com.ineq')
-+load_obj_and_save_ineq('./lhleg_com_reduced.obj', './lhleg_com.ineq')
-+load_obj_and_save_ineq('./rhleg_com_reduced.obj', './rhleg_com.ineq')
-+load_obj_and_save_ineq('./rfleg_com_reduced.obj', './rfleg_com.ineq')
---
-2.17.1
-