Toward commercialization of robotic systems for high-value crops: state-of-theart review and challenges ahead

Transcription

1 Toward commercialization of robotic systems for high-value crops: state-of-theart review and challenges ahead Wouter Bac MSc 27 September 2012 Wageningen UR Greenhouse Horticulture

2 Overview Introduction Plant Maintenance Operations (PMOs) Literature review about harvesting robots 7 factors limiting commercialization 7 future challenges 2

3 Why this review Despite 30 years of research no commercial robots for PMOs in high-value crops why? Quantified performance unknown about state-of-the art Future challenges to commercialize robotic systems for high-value crops 3

4 Literature review demarcation Only high-value crops high labour costs (29 % NL) Only multiple-harvest crops (tomatoes but not lettuce) Only Plant Maintenance Operations (PMOs) Time period

5 Operations in high value crops: PMOs candidate 1. Seeding, grafting and cutting 2. Transplanting 3. Transport of plants to a greenhouse 4. Planting 5. Plant Maintenance Operations PMOs 1. Attaching plants to a supporting wire or stick 2. Sticking support sticks or knotting wires 3. Side shoot removal 4. Fruit/flower thinning 5. Leaf picking 6. Lowering plants 7. Crop protection/spraying 8. Harvesting (single/multiple) 6. Internal transport of plants or harvested products 7. Grading 8. Packing 9. Crop removal and cleaning 5

6 Review Methodology 6

7 Only harvesting robots were reviewed, examples: Cucumber (Van Henten et al., 2003) Strawberry (Hayashi et al., 2010) Cherry (Tanigaki et al., 2008) Melons (Edan, 1994) Egg-plant (Hayashi et al., 2001) 7

8 Methodology Performance indicators Autonomous: true/false Tested in field or lab Fruit localization success [%] Fruit detachment success [%] Cycle time [s] Damage rate [%] Number of fruits evaluated [#] Detachment attempt ratio [total attempts/succesful attempts] 8

9 Methodology (2) Design process techniques Use of systematic design or systems engineering methods: true/false Use of an economic analysis Hardware design decision Manipulator DOFs used Off-the-shelve or custom-made hardware components 9

10 Methodology (3) Algorithms partially or fully reported for: Fruit localization Ripeness determination Obstacle localization Task planning Motion planning Whether any of these algorithms were adaptive: true/false 10

11 Results 11

12 In total, 48 projects have been performed 12

13 Performance indicators Cycle time was 35 ± 57 s (N=26) 13

14 Performance indicators (2) 73 % were autonomous 12.5 % reported the attempts made: avg 1.7 att per fruit 67 % were tested in the field 14

15 Systematic Design/ Economic analysis 12.5 % used a systematic design method 12.5 % performed an economic analysis 15

16 Manipulators mostly 3 DOF 16

17 7 factors limiting commercialization of robotics systems 17

18 Factors 1-3 (quantified proof) 1. Cycle time too long (35 ± 53 s) 2. Fruit localization, detachment, and harvest (65.7 %) did not reach 100 %. What about the other 35 % of the ripe fruits? Lack of learning capabilities 3. Projects poorly reported 57 % of the performance indicators was based on a known number of test samples Number of samples evaluated varied: 11 to 2506 Units missing in 24 % of the reported perf. indicators 18

19 Factors 1-3 (quantified proof) 3. Projects poorly reported Damages to the plant never reported, exception (Pool & Harrell, 1991) False-positive detections hardly reported Requirements hardly described Functionality of the robot hardly described Algorithms hardly described (5-63 %) Algorithms partly described in 49 % of the cases Failed projects never reported 19

20 Factors 4-7 (indications only) 4. Robot designs probably suboptimal Mostly travelling device, manipulator and end-effector Manipulator DOF Alternative designs hardly explored Economics hardly considered 5. Scattered market 6. PMOs differ among crops & limited machine utilization 7. Added value hardly explored 20

21 Future Challenges 21

22 Challenges Modifying the environment Different cultivation systems, e.g. cucumber Supportive mechanisms, e.g. blowers, pushing mechanisms, canopy compression Alternative cultivation methods, e.g. flower pruning to avoid fruit clusters Cultivar selection and cross-breeding 2. Enhancing the robotic system Learning capabilities, e.g. adaptive classifiers, on-line learning algorithms Human-robot collaboration Dedicated hardware, e.g. compliant end-effectors, optimized manipulators 22

23 Challenges Using systematic design Involve stakeholders: growers, engineers, academia Define requirements for several aspects QFD by Toyota; Cradle-to-cradle; etc. Systems engineering (Edan & Miles, 1994) 4. Performing economic analyses System costs Payback time Damages Maintenance costs R&D costs Example: sweet-pepper harvester for 180 6s/fruit 23

24 Challenges Adding value to the robotic system Tracking and Tracing Ripeness prediction Disease detection by chlorophyll fluorescence Sorting and quality assesment directly after harvest Phenotyping tasks 6. Multi-operational or multi-crop systems Apple and peach (Sites and Delwiche, 1988) Cucumber leaf picking and harvesting (Van Henten et al. 2002, 2006) Grape harvesting, spraying, bagging and thinning (Monta, 1995) However, trade-off between cost and machine flexibility (Gupta & Goyal, 1989) 7. Improve knowledge transfer 24

25 Conclusion Operations summarized Only 2 projects for PMOs other than harvesting and spraying 48 harvesting robot projects identified 7 Limiting factors identified 7 Future challenges established 25

26 Thank you for your attention 26