They were able achieve this by borrowing the dynamic walking style from the springbok, a smaller antelope. By using this walking style, the SpaceBok is able to take strides where all its legs are in the air, rather than one leg keeping in contact with the surface.
By Utilizing the organic movements of the springbok, the SpaceBok is able to more efficiently traverse the moon, mars or even asteroids through a series of algorithms and computational power. Although the SpaceBok does have to land at a certain point, through this design it’s able to easily and effortlessly leap through low gravity environments, providing a quicker option for exploring the surface of these environments.
Using springs located on the end of its legs, the robot is able to store energy from landing and immediately launch up to six feet in the air. Borrowing the technology used to stabilize satellites, European Space Agency Engineers created a stability system for SpaceBok. The system, called a reaction wheel, allows the SpaceBok to accelerate or decelerate in different directions to keep the robot oriented. The SpaceBok is being tested in the lab right now, but there are plans to begin testing on hilly terrain soon.
According the Octinion, in the same amount of time it takes a normal human strawberry picker to pick about 100 lb of strawberries, Rubion, the strawberry picking robot can pick nearly 800 lbs. Rubion is able to accomplish this feat through a pre-programmed dataset in its internal RGB camera and a photonic sensor which lets it recognize and distinguish different wave lengths and from those wave lengths, it can determine if the strawberry is ripe or not. Once the robot decides the berry is ripe, it carefully picks the berry using a soft gripper. It then sorts the berry based on its weight and size. This whole process is quickly executed within five seconds called the five-second picking cycle
“Just like you know what a plump, juicy red strawberry looks like, Rubion can do this mathematically,” says Dr. Jan Anthonis, the CTO of Octinion”looking for the infrared spectroscopic heat signatures given off from a perfect fruit, getting a perfect ‘hit’ every time,”
Strawberries and other fragile and soft fruits are tough to automate because not only does the robot need to be capable of determining between under ripe, over rip and rip fruit, the robot also needs to handle it delicately due to easy bruising. Rubion is proficient in locating, gathering and storing the strawberries all without damaging them.
Automation Technologies like Rubion are gaining popularity fast due to labor shortages in the agriculture industry around the world. Many farms don’t have enough workers to pick all their fruits or vegetables so the remaining produce is usually left to rot. There have been many other attempts from different robotics engineering companies at automatic produce harvest like a robot that can pick 25,000 raspberries in a single day, a robot that harvests apples automatically using suctions and a robot that can cut and harvest lettuce. Likewise, rice farmers in Japan are starting to use robotic ducks to diminish weed growth and pesticides in rice fields
The Vegebot has a computer vision system built into it and using its overhead camera, it can identify the head of lettuce and determine whether the lettuce is still growing, ready to harvest or diseased. After the Vegebot determines that the lettuce is ready to harvest, a second camera is used to guide a Universal Robots UR10 arm with a blade anchored to it to cut the head. A gripper or end effector is then used to collect the harvested lettuce from the ground.
While this prototype was success in picking the lettuce, researchers admitted that this process currently takes more time and is less efficient that using human workers and still needs a lot of work. Harvesting lettuce automatically is an arduous problem to solve because the heads grow low to the ground making it difficult to cut and they can be easily damaged during handling.
The researchers at Cambridge were able to use a set of lettuce images to train the Vegebot to recognize and classify diseased or infected heads of lettuce through a machine-learning algorithm. They were also able to teach the Vegebot the proper grip to employ when handling the delicate crop so it doesn’t get damaged. Although not fully complete yet, the Vegebot and other robotic harvesters could not only help relieve labor shortages in the farming industry but it could also diminish food waste. Instead of picking the whole field in one pass, forthcoming iterations, according to researchers will be able to continuously and repeatedly analyze and harvest fully developed vegetables
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