Scientists have developed a robot with a 3D camera and two arms equipped with grippers that can autonomously put together ready-to-assemble furniture without interruption.
The robot assembled a ‘build-it-yourself’ chair in 8 minutes and 55 seconds. Prior to the assembly, the robot took 11 minutes and 21 seconds to independently plan the motion pathways and 3 seconds to locate the parts.
“The job of assembly, which may come naturally to humans, has to be broken down into different steps, such as identifying where the different chair parts are, the force required to grip the parts, and making sure the robotic arms move without colliding into each other,” said Pham Quang Cuong, assistant professor at Nanyang Technological University in Singapore.
“Through considerable engineering effort, we developed algorithms that will enable the robot to take the necessary steps to assemble the chair on its own,” said Mr. Pham.
“We are looking to integrate more artificial intelligence into this approach to make the robot more autonomous so it can learn the different steps of assembling a chair through human demonstration or by reading the instruction manual, or even from an image of the assembled product,” said Mr. Pham.
Researchers believe that their robot could be of greatest value in performing specific tasks with precision in industries where tasks are varied and do not merit specialised machines or assembly lines.
The robot is designed to mimic the genericity of the human “hardware” used to assemble objects: the ‘eyes’ through a 3D camera and the ‘arms’ through industrial robotic arms that are capable of six-axis motion.
Each arm is equipped with parallel grippers to pick up objects. Mounted on the wrists are force sensors that determine how strongly the “fingers” are gripping and how powerfully they push objects into contact with each other.
The robot starts the assembly process by taking 3D photos of the parts laid out on the floor to generate a map of the estimated positions of the different parts.
This is to replicate, as much as possible, the cluttered environment after humans unbox and prepare to put together a build-it-yourself chair. The challenge here is to determine a sufficiently precise localisation in a cluttered environment quickly and reliably.
Next, using algorithms developed by the team, the robot plans a two-handed motion that is fast and collision-free. This motion pathway needs to be integrated with visual and tactile perception, grasping and execution.
To make sure that the robotic arms are able to grip the pieces tightly and perform tasks such as inserting wooden plugs, the amount of force exerted has to be regulated. This is challenging because industrial robots, designed to be precise at positioning, are bad at regulating forces, Pham said.
The force sensors mounted on the wrists help to determine the amount of force required, allowing the robot to precisely and consistently detect holes by sliding the wooden plug on the surfaces of the work pieces, and perform tight insertions.
The robot, described in the journal Science Robotics, is being used to explore dexterous manipulation, an area of robotics that requires precise control of forces and motions with fingers or specialised robotic hands. As a result, the robot is more human-like in its manipulation of objects.
So far, autonomous demonstration of dexterous manipulation has been limited to elementary tasks, said Pham.