Lettuce picking robot
Automation has revolutionised the farming industry, but some crops, like lettuces, have proved tricky to harvest in any way other than by hand. Now that might be about to change, with the help of a new robot. Heather Jameson has been to the Cambridge University Engineering Department to hear how ...
Heather - Billions of lettuces are produced globally every year and every one has been picked by hand. Whilst harvesting of other crops such as wheat and potatoes has for a long time been automated, lettuces have so far eluded automation for various reasons. Firstly, lettuces are very easily damaged and supermarkets have very high standards for what they will accept. Secondly, if you imagine looking out at a field of lettuces all you see is a sea of leaves. It's actually very difficult to pick out individual lettuces even for humans. But now engineers at Cambridge University have developed a robot which they believe is up to the task. At the end of a large robotic arm, the robot has a square cage, big enough for a football, and the cage does the cutting and collecting. The robot also has two cameras to see the lettuces. Simon Birrell showed me how it worked.
Simon - So this cage that you see, this is what we call the end effector at the end of the robot arm. This goes down over the top of the lettuce. At the top we have a valve attached to compressed air. So when the robot decides it's time to grasp, it activates the valve and this soft gripper, which is covered in silicone, comes over and grabs the lettuce and it grabs it gently so that it doesn't bruise it. And then the valve is activated again and this rotary belt goes round and it drives this blade down here, through the stalk of the lettuce and goes through and gives it a clean cut.
Heather - But before the robot picks the lettuce, it first has to find it in the confusing sea of leaves and then decide whether the lettuce is good for harvesting. The robot has been trained to identify the lettuces using neural networks. A neural network is a computer system which is inspired by the way the human brain works.
Simon - It classifies the lettuce into good - suitable for harvesting now, immature - which is a lettuce that we’ll come back for later when it's grown a bit, and a diseased lettuce. It's very important not to pick a diseased lettuce, because if you do, you can contaminate the end effector and then when you move it to the next lettuce, you run the risk of spreading mildew or whatever the infection is.
Heather - At the moment the cutting process is not intelligent, it's a pre-programmed process. But in future the engineers would like the robot to also be able to learn to cut more accurately as well.
Simon - The supermarkets are extremely picky about what the cut looks like. So the cut can't be too close to the lettuce head. It can't be too far away. It's got to be at 90 degrees. All of this is nonsense in many ways. I mean, the lettuce still tastes exactly the same. But, yes, we are interested in adding neural networks so that it can learn the best way to cut and continuously improve the way it does it.
Heather - The team had tested the robot in the field. Literally, in a field of lettuces. The robot sits on a rig, powered by a generator and the wheels roll between the rows of lettuces.
Simon - Conditions are totally different from the lab. You have wind, you have dust, you get rained on... everything is bumpy so that all the equipment gets knocked around a lot. So all the kind of fine tuned calibration that you do in the lab is completely useless out in the field.
Heather - In the tests, the robot successfully located the lettuces 91 percent of the time and successfully classified them 82 percent of the time. In terms of speed, the robot is currently about four times slower at picking lettuces than a human. But Simon reckons they can easily reduce this difference by changing to a stronger robotic arm. The current arm moves quite slowly because the cage is quite heavy. But whilst the robot will be able to take over the physical demands of harvesting there will still be a role for humans to play.
Simon - There's always going to be a place for humans - in terms of maintaining the robots, and in terms of managing the robots. Particularly if we do learning. One of the things we're considering is having people monitoring remotely a series of robots through video feeds. If they see the robot making a mistake they can call that out and that data then gets incorporated and retrained into the next iteration of the neural network.
Heather - And if you're worried about the robots taking over, Simon kindly pointed out to me that the cage was the perfect size for cutting off human heads… but he hasn't tested this theory out yet.