Add failure_dataset (robot execution failures, 5 lp*.data files)

failure_dataset/lp1.data

@@ -0,0 +1,1582 @@
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failure_dataset/lp2.data

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failure_dataset/lp3.data

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failure_dataset/lp4.data

@@ -0,0 +1,2104 @@
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failure_dataset/lp5.data

@@ -0,0 +1,2952 @@
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+	3	-4	9	7	3	-4
+	6	-8	-5	10	7	-3
+	6	-5	12	10	12	-4
+	6	-5	12	10	12	-4
+	5	-3	1	4	5	-3
+	3	0	3	0	5	-4
+	5	-3	1	4	5	-3
+	3	0	3	0	5	-4
+
+
+collision_in_tool
+	-5	14	-43	-101	-49	17
+	-4	1	6	-2	-2	-4
+	-4	0	12	-2	-1	-4
+	-4	-2	3	0	-1	-3
+	-4	0	10	-2	-2	-4
+	-2	-1	-2	-1	1	-3
+	-4	0	10	-2	-2	-4
+	-2	-1	-2	-1	1	-3
+	-1	1	12	-3	1	-3
+	-1	1	2	-2	2	-3
+	-1	1	12	-3	1	-3
+	-4	0	10	-2	-2	-4
+	-2	-1	-2	-1	1	-3
+	-1	1	12	-3	1	-3
+	-1	1	2	-2	2	-3
+
+
+collision_in_tool
+	36	-4	19	8	53	-2
+	25	2	25	0	37	-3
+	22	-14	13	22	35	-2
+	17	-23	10	32	27	-2
+	7	-8	7	13	13	-3
+	4	6	8	-5	9	-3
+	-5	11	15	-12	0	-4
+	1	-1	4	3	5	-3
+	1	0	4	0	5	-3
+	3	0	-3	1	7	-3
+	0	2	13	-3	2	-3
+	3	-1	1	3	5	-4
+	1	-1	4	1	4	-3
+	1	-1	4	1	4	-3
+	2	-1	3	1	5	-4
+
+
+collision_in_tool
+	-12	17	3	-19	-10	-4
+	-12	12	11	-13	-16	-4
+	-8	3	6	2	-11	-4
+	-4	3	1	0	-6	-3
+	-6	6	9	-2	-5	-5
+	-7	3	3	-2	-10	-3
+	-5	-3	5	10	-7	-3
+	1	0	-1	4	2	-3
+	2	1	6	2	4	-4
+	-1	2	10	1	1	-4
+	-1	2	16	1	1	-4
+	2	-1	4	5	3	-3
+	0	1	3	1	1	-3
+	1	2	9	0	3	-4
+	1	2	9	0	3	-4
+
+
+collision_in_tool
+	-41	21	-5	-23	-59	-4
+	-32	21	-6	-25	-45	-4
+	-21	12	-6	-14	-31	-4
+	-3	-1	2	8	-4	-4
+	0	-1	13	8	1	-3
+	6	-2	14	6	9	-4
+	15	-5	3	15	22	-3
+	-1	1	5	3	1	-4
+	-1	1	6	4	0	-3
+	-2	2	5	1	-2	-3
+	-1	1	2	1	0	-3
+	-3	4	13	-2	0	-3
+	-4	4	3	0	-1	-3
+	-4	3	2	2	-3	-3
+	-2	3	5	0	-2	-3
+
+
+collision_in_tool
+	9	-10	-11	17	7	-4
+	5	0	4	0	7	-4
+	-3	6	-2	-8	-8	-4
+	0	-2	6	4	-2	-4
+	-5	-8	4	14	-8	-4
+	-4	-11	5	18	-6	-3
+	3	2	3	-2	4	-3
+	3	1	1	0	5	-4
+	4	-1	15	3	7	-3
+	5	-3	3	7	10	-3
+	1	1	8	0	3	-4
+	0	0	5	0	3	-4
+	-1	1	-3	-3	-2	-3
+	0	-1	-5	-1	1	-3
+	-1	1	4	0	-1	-3
+
+

failure_dataset/robot

@@ -0,0 +1,134 @@
+1. Title of Database: Robot execution failures
+   Note: it includes 5 different datasets; see 4.
+
+2. Sources:
+   (a) Creators / donors:
+       -- Luis Seabra Lopes and Luis M. Camarinha-Matos
+          Universidade Nova de Lisboa, Monte da Caparica, Portugal
+   (b) Date received: April 1999 
+
+3. Past Usage:
+   (a) Some publications where it was described/used
+       -- Seabra Lopes, L. (1997) "Robot Learning at the Task Level:
+          a Study in the Assembly Domain", Ph.D. thesis, Universidade
+          Nova de Lisboa, Portugal.
+       -- Seabra Lopes, L. and L.M. Camarinha-Matos (1998) Feature 
+          Transformation Strategies for a Robot Learning Problem, 
+          "Feature Extraction, Construction and Selection. A Data Mining 
+          Perspective", H. Liu and H. Motoda (edrs.), 
+          Kluwer Academic Publishers. 
+       -- Camarinha-Matos, L.M., L. Seabra Lopes, and J. Barata (1996) 
+          Integration and Learning in Supervision of Flexible Assembly Systems, 
+          "IEEE Transactions on Robotics and Automation", 12 (2), 202-219. 
+   (b) Indication of what attribute(s) were being predicted 
+       -- The class of execution failure; see 9.
+   (c) Indication of study's results
+       -- Part of the results is concerned with feature transformation; see 4.
+       -- Another set of results is concerned with evaluation of
+          data mining algorithms.
+
+4. Relevant Information
+   -- The donation includes 5 datasets, each of them defining a different
+      learning problem:
+      - LP1: failures in approach to grasp position
+      - LP2: failures in transfer of a part
+      - LP3: position of part after a transfer failure
+      - LP4: failures in approach to ungrasp position
+      - LP5: failures in motion with part
+   -- Feature transformation strategies
+      In order to improve classification accuracy, a set of five feature
+      transformation strategies (based on statistical summary features,
+      discrete Fourier transform, etc.) was defined and evaluated.
+      This enabled an average improvement of 20% in accuracy. The most 
+      accessible reference is [Seabra Lopes and Camarinha-Matos, 1998].
+
+5. Number of instances in each dataset
+   -- LP1: 88
+   -- LP2: 47
+   -- LP3: 47
+   -- LP4: 117
+   -- LP5: 164
+
+6. Number of features: 90 (in any of the five datasets)
+
+7. Feature information
+   -- All features are numeric (continuous, although integers only).
+   -- Each feature represents a force or a torque measured after
+      failure detection; each failure instance is characterized in terms
+      of 15 force/torque samples collected at regular time intervals
+      starting immediately after failure detection; 
+      The total observation window for each failure instance was of 315 ms.
+   -- Each example is described as follows:
+
+                 class
+                 Fx1	Fy1	Fz1	Tx1	Ty1	Tz1
+                 Fx2	Fy2	Fz2	Tx2	Ty2	Tz2
+                 ......
+                 Fx15	Fy15	Fz15	Tx15	Ty15	Tz15
+
+      where Fx1 ... Fx15 is the evolution of force Fx in the observation
+      window, the same for Fy, Fz and the torques; there is a total 
+      of 90 features.
+
+8. Missing feature values: None
+   
+9. Class distribution: percentage of instances per class in each dataset
+   -- LP1: 24% normal
+           19% collision    
+           18% front collision
+           39% obstruction
+   -- LP2: 43% normal
+           13% front collision
+           15% back collision
+           11% collision to the right
+           19% collision to the left
+   -- LP3: 43% ok
+           19% slightly moved
+           32% moved
+            6% lost
+   -- LP4: 21% normal
+           62% collision
+           18% obstruction
+   -- LP5: 27% normal
+           16% bottom collision
+           13% bottom obstruction
+           29% collision in part
+           16% collision in tool
+           
+10. File format
+
+   -- The file format is as follows:
+
+           <Number of examples> <Example 1> <Example 2> .... <Example N>
+
+      Each example is described as explained in 7.
+
+   -- In order to convert the files to a more standard format,
+      the following C program is provided:
+
+      #include <stdio.h>
+
+      char str[128];
+
+      main(int argc,char **argv)
+      {
+      
+         FILE *f1, *f2;
+         int i,j,Nex;
+         int aux;
+      
+         f1 = fopen(argv[1],"r");
+         f2 = fopen(argv[2],"w");
+      
+         fscanf(f1,"%d",&Nex);
+      
+         for(i=0; i<Nex; i++) {
+           fscanf(f1,"%s",&str[0]);
+           for(j=0; j<90; j++) {
+             fscanf(f1,"%d",&aux);
+             fprintf(f2,"%d,",aux);
+           }
+           fprintf(f2,"%s\n",str);                     
+         }
+      }
+

failure_dataset/robotfailure.data.html

@@ -0,0 +1,179 @@
+<!------------------------------------------------------------------------
+<!  Robot Execution Failures 
+<!----------------------------------------------------------------------->
+<HTML> <HEAD>
+<TITLE> Robot Execution Failures </TITLE>
+</HEAD>
+<BODY BGCOLOR="#FFFFFF">
+
+<!------------------------------------------------------------------------
+<!  Title 
+<!----------------------------------------------------------------------->
+<H1> Robot Execution Failures </H1>
+
+
+<!------------------------------------------------------------------------
+<!  Data Type 
+<!----------------------------------------------------------------------->
+<H2>Data Type</H2>
+multivariate time series
+
+<!------------------------------------------------------------------------
+<!  Abstract 
+<!----------------------------------------------------------------------->
+<H2>Abstract</H2>
+<p>
+This dataset contains force and torque measurements on a robot after failure detection. Each failure is characterized by 15 force/torque samples collected at regular time intervals starting immediately after failure detection.
+</p>
+
+<!------------------------------------------------------------------------
+<!  Sources
+<!----------------------------------------------------------------------->
+<H2> Sources</H2>
+<H4> Original Owner and Donor</H4>
+<PRE>
+Luis Seabra Lopes and Luis M. Camarinha-Matos
+Universidade Nova de Lisboa, 
+Monte da Caparica, Portugal
+</PRE>
+<B>Date Donated: </B> April 23, 1999 
+
+<!------------------------------------------------------------------------
+<!  Data Characteristics 
+<!----------------------------------------------------------------------->
+<H2> Data Characteristics</H2>
+
+The donation includes 5 datasets, each of them defining a different learning problem:
+<UL>
+<li> LP1: failures in approach to grasp position </li>
+<li> LP2: failures in transfer of a part </li>
+<li> LP3: position of part after a transfer failure </li>
+<li> LP4: failures in approach to ungrasp position </li>
+<li> LP5: failures in motion with part </li>
+</UL>
+
+<H4>Feature information </H4>
+<P>
+All features are numeric although they are integer valued only.
+Each feature represents a force or a torque measured after
+failure detection; each failure instance is characterized in terms
+of 15 force/torque samples collected at regular time intervals
+starting immediately after failure detection; 
+The total observation window for each failure instance was of 315 ms.
+</P>
+
+Each example is described as follows:
+<PRE>
+                 class
+                 Fx1	Fy1	Fz1	Tx1	Ty1	Tz1
+                 Fx2	Fy2	Fz2	Tx2	Ty2	Tz2
+                 ......
+                 Fx15	Fy15	Fz15	Tx15	Ty15	Tz15
+</PRE>
+<P>
+where Fx1 ... Fx15 is the evolution of force Fx in the observation
+window, the same for Fy, Fz and the torques; there is a total 
+of 90 features.
+</P>
+<H4> Number of instances in each dataset</H4>
+<PRE>
+   -- LP1: 88
+   -- LP2: 47
+   -- LP3: 47
+   -- LP4: 117
+   -- LP5: 164
+</PRE>
+
+
+<H4>Class Distribution</H4>
+<PRE>
+   -- LP1: 24% normal
+           19% collision    
+           18% front collision
+           39% obstruction
+   -- LP2: 43% normal
+           13% front collision
+           15% back collision
+           11% collision to the right
+           19% collision to the left
+   -- LP3: 43% ok
+           19% slightly moved
+           32% moved
+            6% lost
+   -- LP4: 21% normal
+           62% collision
+           18% obstruction
+   -- LP5: 27% normal
+           16% bottom collision
+           13% bottom obstruction
+           29% collision in part
+           16% collision in tool
+</PRE>
+
+<!------------------------------------------------------------------------
+<!  Other Relevant Information 
+<!----------------------------------------------------------------------->
+<H2> Other Relevant Information</H2>
+
+<H4>Feature transformation strategies</H4>
+
+In order to improve classification accuracy, a set of five feature
+transformation strategies (based on statistical summary features,
+discrete Fourier transform, etc.) was defined and evaluated.
+This enabled an average improvement of 20% in accuracy. The most 
+accessible reference is [Seabra Lopes and Camarinha-Matos, 1998].
+
+
+<!------------------------------------------------------------------------
+<!  Data Format 
+<!----------------------------------------------------------------------->
+<H2>Data Format</H2>
+The data is stored in five ASCII files, with each example in the files described as follows:
+<PRE>
+                 class
+                 Fx1    Fy1 Fz1 Tx1 Ty1 Tz1
+                 Fx2    Fy2 Fz2 Tx2 Ty2 Tz2
+                 ......
+                 Fx15   Fy15    Fz15    Tx15    Ty15    Tz15
+</PRE>
+where Fx1 ... Fx15 is the evolution of force Fx in the observation
+window, the same for Fy, Fz and the torques; there is a total
+of 90 features.
+
+<!------------------------------------------------------------------------
+<!  Past Usage 
+<!----------------------------------------------------------------------->
+<H2>Past Usage</H2>
+<p>
+Seabra Lopes, L. (1997) "Robot Learning at the Task Level:
+a Study in the Assembly Domain", Ph.D. thesis, Universidade
+Nova de Lisboa, Portugal.
+</p>
+
+<p>
+Seabra Lopes, L. and L.M. Camarinha-Matos (1998) Feature 
+Transformation Strategies for a Robot Learning Problem, 
+"Feature Extraction, Construction and Selection. A Data Mining 
+Perspective", H. Liu and H. Motoda (edrs.), 
+Kluwer Academic Publishers. 
+</p>
+
+<p>
+Camarinha-Matos, L.M., L. Seabra Lopes, and J. Barata (1996) 
+Integration and Learning in Supervision of Flexible Assembly Systems, 
+"IEEE Transactions on Robotics and Automation", 12 (2), 202-219. 
+</p>
+
+<!------------------------------------------------------------------------
+<!  Signature 
+<!----------------------------------------------------------------------->
+<p>
+<hr>
+<ADDRESS>
+<A href="http://kdd.ics.uci.edu/">The UCI KDD Archive</A><br>
+<a href="http://www.ics.uci.edu/">Information and Computer Science</a><br>
+<a href="http://www.uci.edu/">University of California, Irvine</a><br>
+Irvine, CA 92697-3425 <br>
+</ADDRESS> 
+Last modified: March 11, 1999 </BODY>
+</HTML>

failure_dataset/robotfailure.html

@@ -0,0 +1,41 @@
+<HTML><HEAD>
+<TITLE>Robot Execution Failures</TITLE>
+
+<BODY BGCOLOR="#FFFFFF">
+
+<H1>Robot Execution Failures</H1>
+
+<H2> Abstract</H2>
+<p>This dataset contains force and torque measurements on a robot after failure detection. Each failure is characterized by 15 force/torque samples collected at regular time intervals starting immediately after failure detection.
+
+
+<p><B> Information files:</B>
+
+<UL>
+  <LI> <a href="robotfailure.data.html"> description of the data </a>
+</UL>
+
+<p><B> Data files:</B>
+
+<UL>
+  <LI> <a href="lp1.data"> lp1.data</a> failures in approach to grasp position (27K)
+  <LI> <a href="lp2.data"> lp2.data</a> failures in transfer of a part (15K)
+  <LI> <a href="lp3.data"> lp3.data</a> position of part after a transfer failure (15K)
+  <LI> <a href="lp4.data"> lp4.data</a> failures in approach to ungrasp position (34K)
+  <LI> <a href="lp5.data"> lp5.data</a> failures in motion with part (49K)
+</UL>
+
+
+<p>
+<HR>
+<ADDRESS>
+<A href="http://kdd.ics.uci.edu/">The UCI KDD Archive</A><br>
+<a href="http://www.ics.uci.edu/">
+Information and Computer Science</a><BR>
+<a href="http://www.uci.edu/">University of California, Irvine</a><br>
+Irvine, CA 92697-3425
+</ADDRESS>
+Last modified: April 23, 1999
+</BODY></HTML>
+
+