Robot Execution Failures
Donated on 4/22/1999
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
Dataset Characteristics
Multivariate, Time-Series
Subject Area
Physics and Chemistry
Associated Tasks
Classification
Feature Type
Integer
# Instances
463
# Features
90
Dataset Information
Additional 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 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].
Has Missing Values?
No
Variable Information
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. 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.
Dataset Files
| File | Size |
|---|---|
| lp5.data | 48 KB |
| lp4.data | 32.8 KB |
| lp1.data | 26.7 KB |
| a.out | 23.8 KB |
| lp2.data | 14.3 KB |
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pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset robot_execution_failures = fetch_ucirepo(id=138) # data (as pandas dataframes) X = robot_execution_failures.data.features y = robot_execution_failures.data.targets # metadata print(robot_execution_failures.metadata) # variable information print(robot_execution_failures.variables)
Lopes, L. & Camarinha-Matos, L. (1998). Robot Execution Failures [Dataset]. UCI Machine Learning Repository. https://doi.org/10.24432/C5M89N.
Creators
Luis Lopes
Luis Camarinha-Matos
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.