Robotics & Control in Agriculture Abubakr Muhammad Director, Laboratory for Cyber Physical Networks and Systems Dept of Electrical Engineering SBA School of Science & Engineering Lahore University of Management Sciences (LUMS), Pakistan EE361. Lectures on Control Engineering in Environment & Sustainability Spring 2015, LUMS
Objectives • PLO-7: Environment and Sustainability (PEC ) • Deeper motivation: Connecting technology to real- world and societal grand challenges • Accessible introduction to cutting-edge research • Pay attention to the Right Problems! • Demonstrate how student involvement helps develop high impact research
Outline • Motivation: The importance and context of Agriculture in Pakistan • Precision Agriculture – A systems perspective • Feedback Control in Precision Ag – Auto-steering – Variable rate control • Ag Robotics: A new frontier in farm automation • The case for Automation & Robotics in Pakistan • Conclusions and outlook
Agriculture at the Center Agriculture in Pakistan provides Agriculture • Food • Raw material • Foreign trade Commerce Industry 25% GDP, >50% of population in agriculture Pakistan’s Ag Profile Traditional : Rice, Cotton, Wheat, Sugarcane, Maize Upcoming : Livestock, Fisheries, Forestry, Horticulture
Agricultural Footprint ~25% under cultivation of which 80% is irrigated.
The Green Revolution in the Indus Basin • Irrigation canal networks (pre- and post-partition) • Emergence of agricultural research resulting in High Yield Varieties HYV (1950s) • New “miracle” seeds, fertilizers, mechanization, groundwater pumping, multiple cropping, processing, storage, financial measures etc. (1960s-1980s) • The boat we probably missed was the Gene revolution! (1990s-) (GM crops: herbicide-, disease-, drought-, insect- resistant varieties)
Problems Related to Low Productivity Poor Economics 1. Under-utilization or over-exploitation of cultivable land, manpower 2. Uneconomic holdings (farm sizes) and defective land tenure system 3. Pricing and subsidies Poor Methodologies 1. Insufficient or inefficient use of Inputs (pesticide, fertilizers, seeds, mechanization, irrigation) 2. Water issues: logging, salinity, scarcity 3. Agricultural research and extension / education Poor Infrastructures Rural infrastructures and services ( roads, energy, distribution, storage…) 1. 2. Markets and financial institutions (access, credit, insurance, smuggling) Negative Driving Forces 1. Climate change, droughts, floods and natural disasters 2. Diseases and pests 3. Population growth and demographic transitions 4. Urbanization, globalization
Problems Related to Low Productivity Poor Economics 1. Under-utilization or over-exploitation of cultivable land, manpower 2. Uneconomic holdings (farm sizes) and defective land tenure system 3. Pricing and subsidies Poor Methodologies 1. Insufficient or inefficient use of Inputs (pesticide, fertilizers, seeds, mechanization, irrigation) Robotics, 2. Water issues: logging, salinity, scarcity Automation 3. Agricultural research and extension / education & Control Poor Infrastructures Rural infrastructures and services ( roads, energy, distribution, storage…) 1. 2. Markets and financial institutions (access, credit, insurance, smuggling) Negative Driving Forces 1. Climate change, droughts, floods and natural disasters 2. Diseases and pests 3. Population growth and demographic transitions 4. Urbanization, globalization
The Precision Ag Revolution Measure and respond against variability while optimizing returns. Courtesy. Tristan Perez, QUT, Australia
The Precision Ag Revolution Measure and respond against variability while optimizing returns. Key technologies (1990-2010) • Variable rate input • GPS enabled auto-steering • Satellite imagery • Minimal / No tilling
Control Architecture • ECUs on implements connected via CANBus Courtesy. Crop Protection, Australia
GPS enabled Auto-steer Courtesy. Crop Protection, Australia Inter-row sowing
Using Satellite Imagery for Yield Maps Courtesy. Andrew Robson, UNE
Variable-Rate Treatment • Once mapped, how to act? (see e.g. weed map below) • Variable-rate (local measurements) Vs. Fixed rate (bulk measurement) Ref. De Baerdemaeker et al. IEEE Control Systems Magazine, 2001
Variable-Rate Treatment • Real-time adaptive field spraying over weeds Ref. De Baerdemaeker et al. IEEE Control Systems Magazine, 2001
Automatic Sensing & Spraying Courtesy. Horticulture Innovation Australia, Sugar Research Australia
Active Spray Boom Suspension • Active suspension systems to counter soil unevenness. • The two hydraulic actuators counteract tractor yawing and jolting by moving the sledge in the opposite direction. Ref. De Baerdemaeker et al. IEEE Control Systems Magazine, 2001
Modeling and Control • Textbook quarter-car suspension model • Disturbance, control • Disturbance step response
Control Specification (Freq. Domain) • Tractor accelerations below 0.5 Hz are due to operator maneuvers • Only vibrational modes of the boom below 10 Hz contribute to an uneven spray deposition pattern . • Therefore isolator should attenuate boom accelerations between 0.5 and 10 Hz. Ref. De Baerdemaeker et al. IEEE Control Systems Magazine, 2001
Model Identification • Plant identification • Separate modes – Rotational – Translational
Controller Performance in Field • Sensitivity function E(s) = S(s)R(s) – S(s)G(s)W(s) + T(s)V(s) • Loop shaping • Boom tip movement (with and without control) Ref. De Baerdemaeker et al. IEEE Control Systems Magazine, 2001
Fertilizer Spreader • Precise spreading of liquid menure • Disturbance: Variable vehicle speed • Variability: Slurry setpoint variation Ref. De Baerdemaeker et al. IEEE Control Systems Magazine, 2001
End of Part 1
Agricultural Robotics Courtesy. Eldert Van Henten, Waganengin University
Ag Robotics Platforms • Farm mapping and autonomy • Yield estimation e.g. Almonds and Apples • Tree database e.g. Almonds • Precision weed sensing • Horticulture Courtesy. Horticulture Innovation Australia. CMU. USDA. Usyd, Bulent Ecevit Univ, Technion, Aalto
ACFR Platform
Robotics in Horticulture • Agronomic solutions - crop nutrition, canopy structure, pest numbers/identification, weed detection/removal, yield • Physiological solutions - flowering, fruit set, maturity indices (colour/sugar), forcasting/yield, abiotic stress (cold injury, drought, heat, salinity and metals) • Social solutions – safe, skilled and increased capability Ref. Anthony Kachenko, Horticulture Innovation Australia
Yield Mapping • 3D vision algorithms • Active and Passive Sensing Courtesy. USDA, ACFR
Fruit Picking Automation Courtesy. UC Davis
Automatic weed spot spraying Courtesy. Horticulture Innovation Australia, Sugar Research Australia
Automated Harvesting: Indoor / Greenhouse Courtesy. Eldert Van Henten, Waganengin University
High Trellis Twining • Requires special string and knot for PNW windy environment • Tie on “infinitive” long cable, none similar mechanism usable • Very large number of knots (>4,000/ac) done in a short time window • Operating at a high elevation on unprepared ground surface with wind Courtesy. Qin Zhang. Washington State University
Autonomous Land Vehicles for Demining & Agriculture ALVeDA & MDRD (2010-2013) Collaboration: RRLab, TU Kaiserslautern Funding: DAAD, LUMS, National Instruments Field Experiments: Channel mapping in Lahore (left). Objective: Push performance limits with low-cost vision sensors and simple mechatronics. Scanning a minefield in Beirut (right). Robot Vision: Terrain Classification, RGB-D & Monocular SLAM, Visual Servoing, Soil Estimation in a Bucket Excavator.
Aerial Mapping of Irrigation Canals for Silt Deposition Collaboration: RRLab, TU Kaiserslautern Funding: DAAD, LUMS Examples of Siltation and bank deterioration in the Indus Basin. Motivation: Automation of annual canal cleaning operation in the world’s largest irrigation network. Proposed System Architecture. Guassian Processes (GP) based vol. Localization and navigation (online), estimation Mapping (offline)
Ag Robotics Community • Emerging area: http://www.fieldrobot.com/ieeeras/ • Summer schools (Sydney 2015), workshops, special issues • IEEE AgRA (Robotics & Automation Society) technical committee.
Some Basic Questions … • Why Automation in developing countries like Pakistan? – Devolution of governance – Ensuring rights – Conflict resolution Entitlements Participation • Major challenges – Natural resources – Food and Agriculture – Critical infra-structures Accountability – Security – Healthcare
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