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Abstract:

This dataset contains wrench (6D: force and torque) measurements on a robot after failure detection. Each failure is characterized by 15 force/torque samples collected at regular time intervals

Data Set 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

INFO

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. Number of instances in each dataset

-- LP1: 88

-- LP2: 47

-- LP3: 47

-- LP4: 117

-- LP5: 164

Class Distribution

--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