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 | 10/6/2009 | | |
October 6-7, Tony Koselka, Jillian Cannons, and Ryan Carlon, of Vision Robotics Corporation (VRC) returned to Washington for further field trials of the Newton Scout at Allan Brothers’ Othello Orchard. The purpose of this field trial was to gather data on blush and green apple varieties.
Karen Lewis, WSU Extension Educator and interns with the Washington Tree Fruit Research Commission hand tagged, mapped and sized fruit on several rows of fruit for the groundtruthing or validation component of the test.
Several runs were made over a two day period allowing for a review of previous and newly acquired data. The rows chosen for day two were on a grade of 15-20 degrees. During these runs, the mast had to be manually adjusted for the grade of the orchard. All other runs had been on relatively flat ground.
Vision concluded the field trial by sending Newton down flat rows of green apples. All other field test had been on red to blush apples. This new data will combine with previous data to create a discrete data set.
See Newton go! | Vision Robotics' Scout "Newton" |  | 8/31/2009 | |  |
See atttachment for PDFor Powerpoint Presentation | WeedSeeker Field Trials in PA Pilot Orchards |  | 8/15/2009 | |  |
Vision Robotics has addressed much of the robustness and rigidity issues on Newton by replacing the actuators with steel bracing. The entire mast is now pretty stiff. In addition, we replaced the flash mounts with stronger versions, although they are still made of wood.
It seemed like a good idea for a preliminary field test prior to returning to Washington, so we scouted pomegranates here in Southern California. The platform worked well and even looked solid when moving at speeds up to 5 – 10 mph. If you watched Newton in Moses Lake, this is a significant improvement. We made some changes inside the electronics cabinet, and despite it being another brutally hot day, did not have problems with the computers overheating. We have also improved our process for shipping and data collection in the field and require less time for setup and between runs. I have attached a couple of pictures from the tests.
Unfortunately, the flash units are getting more finicky in that they tend to overheat. In general, we are pushing them beyond the design capabilities. They have a 2 hz frame rate, but it is doubtful that a studio photographer would flash twice a second for several minutes at a time. We know that these are not the flashes for production, so they only have to work for the September field tests. We will create the test plan knowing these limitations. The plan is to be back in WA the week of Sept 28.
Photos Attached. | Vision Robotics Preliminary Field Test |  | 7/30/2009 | | |
July 30, Wenfan Shi, Jim Owen, Heather Stoven, Sanjiv Singh and Karen Lewis conducted initial field testing of the automatic caliper measurement at Cameron Nursery, Eltopia, Washington. Passes through nursery stand of 2 year old grafts were conducted in bright sunlight. Accuracy of <5 mm was achieved at a moving rate of 1 mile per hour. | July Field Test Automated Caliper Measurement |  | 6/25/2009 | |  |
Engineering Solutions Field Day Pilot in Plantings Penn State FREC and C&G Orchards | Engineering Solutions Field Day in Pilot Plantings,PA |  | 6/24/2009 | | |
We conducted a 2-week long field trip to Washington state to test some of the technologies developed by CASC in orchards representative of the national apple industry,. In week 1 we focused on GPS-free row following and turning and vehicle localization. Our initial tests were performed at the Washington State University’s Sunrise Orchard in Rock Island, near Wenatchee. Sunrise was the ideal orchard for us to begin testing, as it provides a variety of row configurations – including narrow and wide and short and long rows, as well as flat and rolling terrain. We selected a relatively narrow, long set of rows located on flat terrain and worked there for three days. Despite overheating issues with the GPS-based ground-truthing system, we were able to successfully demonstrate both row following and row turning without using GPS. Perhaps one of the more important aspects was the successful demonstration of row entry using detection of the row profile prior to actual entry. We also spend significant time collecting data to further our work on GPS-free vehicle localization; we will use the data to assess the performance of the current algorithms and to design enhanced ones. Before we left Sunrise we did some quick row following tests at the more hilly parts of the orchard, not to prove that the APM works there but to collect data that will be later used to make the row following algorithms more robust to terrain inclination.
Next we moved the APM to McDougals’s Roche orchard near Moses Lake for two days of row following and turning tests in anticipation to our week 2 APM-Scout integration tests. Roche is a more challenging orchard than Sunrise in terms of row width and terrain slope; still, we were able to complete a large number of successful row following/turn runs. Turning with detected row entry works mostly well, but does occasionally fail in this orchard. The primary cause appears to be the dense canopy on the trees at the head of the row, which prevent the APM from seeing the rest of the trees in the row and consequently estimating the row profile correctly. We also collected data for the localization work, mostly without cones, in anticipation of using scan matching or trees as landmarks.
On the way from Sunrise to Roche we stopped at two large commercial orchards to get a feeling of the future work we will need to do to adapt the APM to a broader variety of places. In these orchards, the row width is so narrow that the APM cannot traverse without touching leaves, limbs, or fruit. While we may be able to use the existing autonomy algorithms to drive in these blocks, we will certainly need to deploy them on a vehicle of a different form factor. This is actually one of the objectives of the project – to map the APM autonomy architecture to platforms that attend a variety of needs and that are able to traverse rows of different shapes and sizes.
While at Sunrise we participated in WSU’s Sunrise Research Orchard Field Day, organized by the orchard director Jay Brunner and WSU faculty. The program included talks and demonstrations on apple breeding, biological control, crop load management, robotic systems (i.e., CASC), apple replant, and orchard development. | Field Trip, Washington State Week 1 |  | 6/22/2009 | | |
We have conducted a week long field trip at the Penn State Fruit Research and Extension Center in Biglerville, PA to test various technologies we have been developing over the past year. We demonstrated row following as well as deployment of a tow-behind mower as well as an intelligent weed sprayer. We have also used the APM to collect data that will be used to detect plant stress.
On one long run, the APM ran for four hours in autonomous mode with a few interruptions. We have found the need to improve robustness of automatically finding the row to enter when skipping rows and the thermal issues on the low-level controller while significantly decreased, still persist. Distance covered autonomously on this field trip: 34 km
We also participated in a set of demonstrations for a group of growers. Pictures from the field day are available here.
Total distance traveled autonomously (2009): 85 km | Biglerville, PA - June 22-26, 2009 |  | 6/5/2009 | | |
We have been testing at Soergel Orchards once a week for the past month. On June 5 our aim was to test three items: (1) recent modifications to the row following algorithm; (2) the mechanical integration of the APM and a wagon that will carry vision sensors; and (3) preliminary GPS-free accurate positioning code.
Row and edge following are now improved. The APM traversed 13 rows following the center and 14 rows following edges for a total of 4.8 km autonomous travel.
With the wagon attached, the APM is able to execute turns with a 3 m radius from one row to another during autonomous row following (see first movie).
Localization (GPS-free positioning) is done with the help of reflective cones placed in the rows. At the end of the day, the APM was commanded to follow a row at low speed to facilitate our "cone picking" (see second movie). Although people are within the field of view of the laser scanners mounted on the front of the vehicle, the row detection algorithm is able to filter out them out and find the rows of trees correctly.
Total distance traveled autonomously (2009): 31.2 km | Soergel Orchards, Wexford, PA - June 5, 2009 |  | 4/16/2009 | | |
We experimented with automated prime mover at Half Crown Hill orchard, a small apple orchard located near the Pittsburgh Airport. This orchard has young trees in planted in rows varying from 15 to 16 feet space in between the trees. The orchard is planted on a significant but flat slope. The trees themselves are grown in a vertical X formation. That is they use dwarfing stock that keeps the trees from growing very tall. At this time of the year, the trees are bare and blooms are expected in a few weeks.
We were testing autonomous driving in the row using a new configuration of lasers scanners than we have used before. Row following was stable at 1 m/s (approx 2.25 mph) in the middle of the rows. We found two issues to resolve-- turning at the end of the rows was problematic because there is not a lot of room at the end of the rows. We found that the automated steering has a problem at the tightest curvatures. Also, rows with uneven ends (left and right rows don’t end at the same distance) have not been considered in the end of row turns. Total distance traveled under autonomous mode = 1.1 km. | Half Crown Hill Orchard - April 16, 2009 |  | 3/25/2009 | | |
We have used the laser data collected at Soergel Orchard to simulate row following. The distinction of this work is that it doesn’t assume accurate positioning or a accurate path that has been provided in terms of GPS coordinates. Onboard laser scanners are used to estimate the the edges of the row and steer the vehicle either in the middle of the row or to follow one side of a row. This capability is important because getting accurate positioning is expensive, especially in the case of tall vegetation. We expect to test this capability in an orchard in April 2009. | Simulated Row Following - March 25, 2009 |  | 3/24/2009 | | |
The latest APM is based on an MDE Workman made by Toro. The vehicle has been retrofitted into a “drive by wire” machine such that it can be controlled by computer commands. It also has been retrofitted with two single axis laser scanners mounted on the front bumper. In this test we controlled the vehicle’s steering and speed and tested the braking using commands from a remote computer connected wirelessly to the machine. We expect to add various sources of positioning (GPS, inertial) and a rugged laptop to this machine in the near future. We will also install a generator on the rear bed for extended duration operation. The main improvement from the previous workman is that the electrical components for vehicle control have been weather proofed and installed under the hood with attention to weatherproofing. | APM Testing, Pittsburgh, PA - March 24, 2009 |  | 11/24/2008 | | |
This visit was to acquire range data in an orchard using laser scanners onboard the utility vehicle. The range data will be used to develop guidance, localization and obstacle detection algorithms. We took data in traditional sections of the orchard as well as in the new “vertical X” sections. We focused on collecting range data rather than demonstrating autonomous motion. For now, we are using cones with reflective tape as markers for localization. The cones are not surveyed in anyway and are added to the rows simply to provide reliable features at a regular interval. Laser range data from the vehicle is shown in a registered frame on the right. | Soergel Orchards, Wexford, PA - November 24, 2008 |  | 11/14/2008 | | |
We did our first autonomous run at Soergel Orchards using an electric utility vehicle that has onboard computing and sensing. The path followed was 1.3 km long using GPS waypoints at speeds between 2 and 3 m/s. The path was four 150 m legs in rows spaced about 26 feet between centers. | Soergel Orchards, Wexford PA - November 14, 2008 |  | 11/6/2008 | | |
Objective: Meet with Penn State University members of the project and visit apple growers and an apple packing facility.
1. Bear Mountain Orchards Met with Joy Cline, orchard manager. BMO has 1,000 acres of fruit trees, of which 480 acres are apples and 280 acres are peaches. About 70% of the apple trees are already in the vertical axis (“tree wall”) architecture. This percentage is expected to increase to 100% in the future. On their tree walls BMO uses M9 root stock grafted with many different varieties of apples. The tree spacing is 6 x 16 ft. The trees are not expected to grow more than 4 ft. to the sides so all fruit get plenty of sunshine. On the traditional tree architecture the spacing is 6-7 x 16-19 ft. and the root stock is M26. Apple harvest takes 45 people, separated in four groups. Three groups are paid by volume to pick apples for processing; one group is paid by hour to pick apples for the fresh market. This allows the pickers working on the fresh market apples to be careful with the fruit and avoid bruising. This is a challenge to any automation solution, which would have to meet the (low) human bruising standards. Joy suggested that we first develop a thinning-assistive device rather than a harvest-assisting device, since during thinning the fruit is simply let to fall on the ground.
2. Adams County Nursery Met with Chris Baugher to see the Blueline platform. The platform has a crude mechanical-feedback device to keep it near one side of the tree row. It only works for tree walls, not for traditional tree architectures. Thinning and pruning are the two activities that have benefited the most from the platform. The tree walls are held in place by thin (1/2”?) metal rods rather than thick (1”?) wooden poles as at BMO. They have old tree walls that they want to make narrower so they can mechanize it.
3. Hollabaugh Bros. Met with Bruce Hollabaugh. They are trying for the first time a high-density tree wall with spacing 4.5 x 14 ft. Problem: vehicles cannot turn around inside row, must go all the way to the end to maneuver. The Hollabaugh’s don’t use ladders and limit their tree sizes to 7.5 ft. Bruce mentioned that one of the obstacles to the introduction of new automation technology is the legacy of all the equipment that growers already have. Different growers own different sets of equipment, suited for their row architectures (especially row separation). Every new automation technology would have to be studied and introduced on a case-by-case basis. Another challenge for automation: some apple varieties are more robust to bruising than others.
4. PSU Fruit Research and Extension Center Met with Henry Ngugi. Henry presented the research on pest and tree disease detection and prevention, including the experiments being done at the FREC greenhouse.
5. Adams County Nursery
Met with Phil Baugher and visited the apple tree nursery. This field has 10,000 trees. They are grafted in the field and sold after two years of growth. Trees are dug in September and sold in January. During these four months they are counted, measured, sorted, and stored in a warehouse. Sorting is by diameter: 3/8”, 1/2", 5/8”, 3/4". Trees are sold one year before they are actually shipped, and by the time of sale the nursery does not have an estimate of how many trees of each diameter they will have available to deliver. They cannot measure tree diameter in the field because it is prohibitively expensive to measure their 700,000 trees. (Nurseries in CA have 1.5 million trees.) If they could do it, they would be able to control inventory much more accurately. Tree separation is 12” x 42”. Main challenges to diameter measurement are double trunks and thick weeds (see pictures at the project AFS space). Asian pears, for example, are very sensitive to weed killers and therefore weed sprays have to be used sparingly. Tree diameter is measured 1.5” above graft and in the direction of the largest semi-axis. The nursery runs a John Deere 6000 (not sure what machine this is) which we could use to install sensors.
6. Rice Fruit Company Met first with Daniel Rice and Lee Showalter, and later with John Rice (CEO). Rice packs 1.5 to 2 million boxes of fruit annually, mostly apples plus pears, peaches, and nectarines. They use a 2-step process: a bulk characterization of fruit by size and color, after which the fruit are stored in an atmosphere-controlled warehouse for up to one year before being sold. The sorting process is almost entirely automated, using machinery from New Zealand that handles 23 tons of fruit/hour. John Rice mentioned that fruit bruising is the single most important factor to impact fruit value. Mechanical harvesting never worked because apples get bruised if they fall on a hard surface from 3”. Harvest takes some 10 weeks of the year, and requires specialized labor. USA apples compete with fruit from Chile, China, and New Zealand. Chinese growers have no credible system for disease inspection. Mexico will start buying apples from China, which could end up in the US. Rice would like to be able to detect internal breakdown during storage, which is invisible to the customer until he/she buys the fruit. Breakdown detection is not a trivial task since humans cannot do it, and therefore there is no process to build from. Rice imagines that vision technologies (especially IR) could address the problem. Food traceability is starting to become an issue. RFC can trace an apple back to the orchard it came from but not to the individual blocks (not to mention individual trees) in the orchard.
| Biglerville, PA - November 6, 2008 |  | 10/17/2008 | | |
Soergel Orchards grows apples using various tree architectures and has a variety of terrain. Reid Soergel has agreed to allow us to test our technology at their facility. This trip was to learn about the facility and growing practices. | Soergel Orchards, Wexford PA - October 17, 2008 |
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