We present RoboGrammar, a fully automated approach for generating optimized robot structures to traverse given terrains. In this framework, we represent each robot design as a graph, and use a graph grammar to express possible arrangements of physical robot assemblies. Each robot design can then be expressed as a sequence of grammar rules. Using only a small set of rules our grammar can describe hundreds of thousands of possible robot designs. The construction of the grammar limits the design space to designs that can be fabricated. For a given input terrain, the design space is searched to find the top performing robots and their corresponding controllers. We introduce Graph Heuristic Search – a novel method for efficient search of combinatorial design spaces. In Graph Heuristic Search, we explore the design space while simultaneously learning a function that maps incomplete designs (e.g., nodes in the combinatorial search tree) to the best performance values that can be achieved by expanding these incomplete designs.

Robot design is usually a painstaking process, but MIT researchers have developed a system that helps automate the task. Once it's told which parts you have--such as wheels, joints, and body segments--and what terrain the robot will need to navigate, RoboGrammar is on the case, generating optimized structures and control programs. To rule out "nonsensical" designs, the researchers developed an animal-inspired "graph grammar"--a set of rules for how parts can be connected, says Allan Zhao, a PhD student in the Computer Science and Artificial Intelligence Laboratory. The rules were particularly informed by the anatomy of arthropods such as insects and lobsters, which all have a central body with a variable number of segments that may have legs attached. RoboGrammar can generate thousands of potential structures based on these rules.

A new MIT system allows robot creators to simulate different robotic forms to determine which one will work best for their desired outcome. The system, called RoboGrammar, simulates different robotic forms after developers key in the parts they want to use for their robot as well as the type of terrain their robot will need to navigate. "Robot design is still a very manual process," Allan Zhao, the paper's lead author and a PhD student in the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), explains in a press release. Zhao describes RoboGrammar as "a way to come up with new, more inventive robot designs that could potentially be more effective." The team at MIT says that the primary inspiration for RoboGrammar came from the animal kingdom rather than from other robot designs -- arthropods such as spiders and lobsters in particular.

"Robot design is still a very manual process. RoboGrammar is a way to come up with new, more inventive robot designs." The way humans move effortlessly can obscure them of the complex motions of the joints and limbs. One would be shocked if they were to build a robot considering all the degrees of freedom, the weight of the payload, 3D geometry and more. The sophisticated designs of robots have been more or less the same.

BEGIN ARTICLE PREVIEW: MIT researchers have automated and optimized robot design with a system called RoboGrammar. The system creates arthropod-inspired robots for traversing a variety of terrains. Pictured are several robot designs generated with RoboGrammar. Credit: Massachusetts Institute of Technology So you need a robot that climbs stairs. What shape should that robot be? Should it have two legs, like a person? Or six, like an ant? Choosing the right shape will be vital for your robot’s ability to traverse a particular terrain. And it’s impossible to build and test every potential form. But now an MIT-developed system makes it possible to simulate them and determine which design works best. You start by telling the system, called RoboGrammar, which robot parts are lying around your shop—wheels, joints, etc. You also tell it what terrain your ro

Researchers at MIT have developed a way for a computer to essentially design its own robotic body, based on the available parts and the local terrain. Dubbed RoboGrammar, the system knows what obstacles it'll need to cover and what equipment is available, and work everything else out from there. The paper's lead author, Allan Zhao, told MIT News said that despite the variety of tasks robots are used for, their designs tend to be "all very similar in their shape or design." Robots are frequently designed to mimic people, animals (with four legs) or vehicles, with wheels and tracks to move around. But that may not be the most useful or efficient form, which is why RoboGrammar's only limitation is the practical limits around building robots.

RoboGrammar is a new system that automates and optimizes robot design. The system, developed at MIT, creates arthropod-inspired robots for traversing a variety of terrains. It could spawn more inventive robot forms with enhanced functionality.