Table 4 System performance evaluation under different payload conditions.

From: Design and implementation of a 6-DoF robot arm control with object detection based on machine learning using mini microcontroller

Weight (g)

Distance (mm)

Time (s) (Avg. ± SD)

Operation Power (W) (Avg. ± SD)

Number of Trials (N)

Success Rate (%)

95% Confidence Interval

Environmental Conditions (during testing)

100

100

0.4 ± 0.02

96 ± 1.5

20

100

[83.8%, 100.0%]

Consistent Indoor Lighting, Varied Backgrounds (trained model), Std. Lab Temp/Hum

200

100

0.4 ± 0.03

96 ± 1.8

20

100

[83.8%, 100.0%]

Consistent Indoor Lighting, Varied Backgrounds (trained model), Std. Lab Temp/Hum

300

100

0.5 ± 0.04

100 ± 2.0

20

100

[83.8%, 100.0%]

Consistent Indoor Lighting, Varied Backgrounds (trained model), Std. Lab Temp/Hum

400

100

0.7 ± 0.05

102 ± 2.5

20

95

[75.1%, 99.9%]

Consistent Indoor Lighting, Varied Backgrounds (trained model), Std. Lab Temp/Hum

500

100

1.2 ± 0.06

108 ± 3.0

20

90

[69.9%, 98.2%]

Consistent Indoor Lighting, Varied Backgrounds (trained model), Std. Lab Temp/Hum