Professor Hadas Kress-Gazit has a kind of “hands-off” approach when it comes to robotics.
Kress-Gazit wants to give a robot a goal – find the green object, for example – and then let the robot decide, on its own, how to accomplish the task.
How can a robot have so many movement and behavior options to choose from exactly?
Kress-Gazit and her fellow researchers at Cornell University and the University of Pennsylvania are developing modular robots – ones that change their shape based on a given task or given surroundings.
“This is the first time modular robots have been demonstrated with autonomous reconfiguration and behavior that is perception-driven,” said Kress-Gazit, an associate professor at Cornell. Research results were published on Oct. 31 in Science Robotics.
The robots feature wheeled, cube-shaped modules that magnetically detach and reattach to form new shapes with different capabilities.
The interchangeable modules, developed at the University of Pennsylvania, are connected to a sensor module. Additionally, the modules are equipped with multiple cameras and a small computer for collecting and processing data about its environment.
A high-level planner in the software directs the robot’s actions, reconfiguration, as well as perception algorithms that can map an environment.
Once the robot is given a task, the planner searches an open-source library consisting of 57 possible robot configurations and 97 behaviors, including “pickUp,” “highReach,” drive, or drop.
Perhaps “Proboscis,” where a long arm moves to the front of the robot, is required. Or maybe the modules need to be arranged in “Scorpion” mode, with perpendicular lines and a horizontal row in front.
In the first of three experiments, a robot was instructed to find and deliver all pink and green objects to a designated zone marked in blue. The robot used the “Car” configuration to explore the area, and then morphed itself into “Proboscis” to retrieve the target from a narrow pathway.
Although the effort took 24 tries, a second experiment demonstrated that a modular robot could autonomously place a circuit board in a mailbox – one that was marked with pink tape and fixed at the top of a staircase.
The Cornell and UPenn researchers found that the hardware and low-level software were the technology components most prone to error, especially when dealing with more complex obstacles like a set of steps.
If such issues are resolved, however, Kress-Gazit said the robots could someday support search-and-rescue applications, especially in environments with uncertain and unpredictable terrain.
Kress-Gazit told Tech Briefs, via email, about the “great promise” of modular robots, especially when they have greater autonomy. The professor’s edited responses are below.
Tech Briefs: What does “modular” mean exactly?
Professor Hadas Kress-Gazit: It means that the robots are created by connecting different pieces, or modules, into larger shapes. In the images and videos, each white cube is a module.
Tech Briefs: Compared to the robots out there today, what is special about your robot?
Prof. Kress-Gazit: The modular robot can be connected to create different shapes. Some examples for robot shapes: We can create a snake robot (modules connected in a line), a rolling wheel robot (a “snake” where we attach the last module to the first) and a quadruped (modules connected to form 4 legs, and then connected to a few modules that form a body) .
Tech Briefs: How are the shapes made?
Prof. Kress-Gazit: Our robot is created by connecting cube faces. Any shape that can be built by putting cubes next to each other can be built. The robot chooses which shape to use based on the task it is trying to perform and the environment in which it is operating.
There are three key technological pieces to our work:
- Hardware design, which is the technology that enables the building of the modules and the reversible connections between them (based on electro-permanent magnets).
- Perception algorithms that, given the sensor information (camera images, depth information), reason about what the environment looks like and whether the robot can perform its task in the environment.
- A high-level planner that, given a task, decides on the shape and control of the robot.
Tech Briefs: What are the autonomous decisions that the robot is making? What is the robot “deciding” exactly?
Prof. Kress-Gazit: The robot takes in information from its sensors and, based on that and the overall task that we gave it, decides how to act. The actions include motion (where to move, how to control the motors to create the desired movement), which is a decision all autonomous robots make, as well as reconfiguration – how to reshape its own body. The reconfiguration actions are unique to modular robots.
Tech Briefs: How is the modular robot able to perceive its surroundings to make these decisions?
Prof. Kress-Gazit: The robot has an onboard RGBD camera that provides images and depth information, and a camera that is pointed at the robot's body to allow for autonomous reconfiguration.
Tech Briefs: What applications do you envision with this kind of robot?
Prof. Kress-Gazit: The great promise of autonomous modular robots is their flexibility and ability to change shape. Applications that require the robot to adjust its shape and behavior based on the environment are especially suitable for this type of robot, and they include disaster relief and exploration of challenging environments.
What do you think about the possibilities of modular robots? Share your comments and questions below.