As the largest on-line retailer in the world, Amazon has numerous warehouses stocked with millions of items that must be ready to be packed and shipped at a moment's notice. With ever-increasing demand for online shopping, automating the object handling system in warehouses will be a necessity. Robots that can autonomously pick up the desired objects from shelves may be able to assist human workforce at warehouse and to increase the efficiency of it. Companies that require wearhouse automation, in addition to Amazon, can also effectively utilize robotic solutions. To this end, the Amazon Robotics Challenge has become an excellent venue for research groups and companies to show case their latests solutions and compete against the best. The specifics of the challenge have developed over the iterations, but the general concept is autonomous picking and stowing from storage systems and packaging boxes.
2017 Amazon Robotics Challenge
2016 Amazon Picking Challenge
For the second iteration of the APC 16 companies and research organizations from three continents participated in the Amazon Picking Challenge preliminary stages. The most outstanding teams earned the right to compete at the finals at Robotcup 2016, Leipzig, Germany. The finalists included renowned robotics groups such as Delft and Nimbro. The challenge consisted of 2 tasks: a pick task to remove 12 specific items from an Amazon Robotics shelf and place them into a tote, and a stow task to move 12 items from a tote and place them into a partially full shelf. For the stow task 12 units started in the tote and the remainder were in the shelf. The items could be stowed to any bin so long as their final location was correctly output by the system. For the pick task all 46 units started in the shelf. One item from each of the 12 bins was specified as the target item to be picked and placed into the tote. Before the challenge the teams were given a rough distribution of how many 2 item bins versus 5 item bins there would be, but not told specifics of how items would be arranged.
The item set consisted of 39 different products selected to present a variety of shapes, sizes, weights, and materials. Seven of the products had two copies, making 46 total units in the challenge. Certain items were worth 1 to 3 bonus points because they are harder to grasp.
2015 Amazon Picking Challenge
For the first iteration of the APC over 30 Companies and research organizations from three continents participated in the Amazon Picking Challenge preliminary stages. The most outstanding teams earned the right to compete at the finals at ICRA 2015. The finalists included renowned robotics groups like Mitsubishi Motors, UC Berkeley, Georgia Tech among others. Amazon held the first ever Amazon Picking Challenge at ICRA conference 2015
Team MIT is striving to solve the general problem of autonomously retrieving objects from warehouse-type shelves. With eyes set firmly on that goal, we developed an entry for the Amazon Picking Challenge that has great potential for future real-life application. Team MIT proved the viability of its solution by dexterously and succesfully picking the majority of the requested items during the competition, eventually earning second place. For the Amazon Picking Challenge, Team MIT used an industrial ABB 1600ID robot arm. This robot arm can move not only fast (about 1meter/sec in our competition settings) but also with sub-millimeter precision. The robot has purpose-built canals that allow routing all cables and airlines internally, this enables the robot to perform manoeuvres in tight spaces without risking pulling on a connector. The ABB Company is seeking to push the boundaries of robotics in warehouse scenarios and lent us the robot arm and advice for competition.
Team MIT designed custom robot end-effector "fingers" for the competition. They are made from aviation-grade aluminum, which gives us the right compliance and endurance while also being extremely light weight. At the outer-most end of bottom finger tip is a spatula-like finger nail. With that, the robot can scoop objects from underneath, or grasp objects that are flush against a shelf wall. On the top finger, there is a suction system for sucking up items that are hard to grasp. To utilize this multi-functional fingers, we've defined 7 motion primitives: grasping, suction down, scooping, toppling, push-rotate, etc. The robot autonomously decides which to execute based on target object characteristics. The robot motions are planned with the Drake package developed by the Locomotion Group at MIT.