Pepper Segmentation Results with YOLOv8 instance segmentation model
Peduncle Segmentation Results with YOLOv8 instance segmentation model
Metric
Pepper
Peduncle
mAP@50
92.5%
92.6%
Precision
94.1%
96.26%
Recall
86.0%
85.75%
Quantitative Evaluation of Segmentation Models
Planning Subsystem Testing
Dual Arm Simulation Testing
No.
Result
Simulated Pose (xyz, roll pitch yaw)
Notes
1.
✅
[0.28, -0.46, 0.53, 0.26, -0.26, 0.0]
Success
2
✅
[0.45, -0.63, 0.48, 0.38, 0.43, 0.0]
Success
3
⚠️
[0.3, -0.5, 0.57, -0.46, 0.37, 0.0]
Success, but cutter had risky pathing
4
✅
[0.34, -0.56, 0.57, 0.13, 0.18, 0.0]
Success
5
✅
[0.31, -0.46, 0.46, -0.01, 0.46, 0.0]
Success
6
✅
[0.27, -0.46, 0.49, -0.04, -0.3, 0.0]
Success
7
✅
[0.27, -0.63, 0.49, -0.33, 0.27, 0.0]
Success
8
✅
[0.25, -0.54, 0.45, -0.27, -0.27, 0.0]
Success
9
✅
[0.26, -0.59, 0.45, 0.02, -0.49, 0.0]
Success
10
✅
[0.4, -0.56, 0.45, -0.03, 0.48, 0.0]
Success
Results of Validation Runs in Simulation
Overall SVD Testing
Sl No.
Outcome
Notes
1.
✅
2
❌
Planning – Failed to find valid grasp plan
3
✅
4
✅
5
❌
Perception – Fine Pose estimate incorrect
6
✅
7
✅
8
❌
Planning – Incorrect Grasp Planning
9
❌
Misc – Grasp Failure due to plastic leaves
10
❌
Perception – False Positive Segmentation
Results of Validation Runs with Hardware Setup
Functional Requirement
ID
Performance Requirement
Desired
Actual
Identify, Localize and Prioritize Green Peppers
PR.01
Detect fully visible Peppers > 70% of the time
70 %
86 %
PR.02
Produce estimate pose of green pepper and peduncle within 3 cm of ground truth depth and within 2 cm of other coordinates and upto 30 degrees in each rotation axis
3 cm
2.4 cm
Harvest Green Pepper
PR.04
Reach target green peppers > 70% of the time
70 %
100 % (Sim)80 % (Real)
Minimize Green Pepper Damage
PR.08
Avoids deformation and damage to 90% of picked green peppers
90 %
95 %
Overall Success
PR.09
Avoid visible damage to harvested green pepper > 90% of the time
90 %
100 %
PR.10
Harvest a fully visible green pepper in testbed autonomously within 100 seconds
