A lot of research has already been done to create maps robots can use to navigate a given area, such as estimating the distance between themselves and nearby walls, and planning routes around obstacles, said Fallon. But these maps are developed mostly for a single, one-time use, and can't be adjusted to changing surroundings over time. "If you see objects that were not there previously, it is difficult for a robot to incorporate that into its map," he said.
The team also includes John J. Leonard, professor of mechanical and ocean engineering, and graduate student Hordur Johannsson.
The team previously tested the approach on robots that were equipped with expensive laser scanners, but have since implemented it with a Kinect-type camera in a robotic wheelchair, a portable sensor suit, and a PR2 robot developed by Willow Garage. On these devices, the system can continuously locate the robotic hardware within a 3D map of its surroundings while traveling at speeds of up to 1.5 meters per second.
The Kinect sensor's visible-light video camera and infrared depth sensor scan the robot's surroundings as it moves through a new, unexplored area, while the robot builds up a 3D model of the walls of a room and the objects within it. Map details can include location information about the edges of walls and objects within the walls.
When the robot visits the same area again, the system compares the previous images it has taken with the features of the new image it creates until it detects a match. Once the system has decided on its location, any new features it encounters since it took the previous picture of that location are incorporated into the map by combining new and old images.
While the system is making and updating maps, it is also continuously estimating the robot’s motion by measuring the distance its wheels have rotated, with onboard sensors. The system can determine the robot's position within a building by combining the motion data with visual information from the camera and depth sensor, which also serves as a form of error correction, said Fallon.
Al, thanks for those additional details on the Kinect sensor's limitations. The fact that it doesn't detect objects less than two feet away should not be a deterrence to its use in checking out a new environment for military tasks, such as in advance of first responders. But I'm surprised that it doesn't work well in sunlight--that seems like a major limitation for these applications, and for helping the elderly or disabled, both of which were two applications the MIT team mentions and which occur at least partly in sunlight. I would not be surprised if this research team is working on methods for overcoming that problem, also.
Ann, Used as a tool to aid in developing mobile robots, the Kinect sensor provides a unique type of feedback which can be used in conjunction with flexible I/O, software algorithms and real-time controllers to quickly and easily prototype, test and deploy robotic applications. The development tools already available make it great for prototyping. But while the Kinect is useful for common robot tasks such as obstacle avoidance, like most sensors it also has limitations. For example, the Kinect cannot detect obstacles that are closer than two feet and does not work well in the sunlight. Still great technology at a mind boggling cost.
Al, I agree that obstacle-avoidance and mapmaking software is a big deal. Specifically, the map-making/obstacle avoidance algorithms based on Simultaneous Localization and Mapping (SLAM) techniques mentioned here, which may also be what's behind the tiny swarming robots' mapmaking ability:
One additional area of software innovation for mobile robots is algorithms for obstacle avoidance. Especially in systems where the mobile robot will encounter humans, such as the tire warehousing application, where the robot is "delivering" a completed tire to a storage/retrieval system, the mobile robot can encounter workers during that delivery process. The software to control those interactions are interesting and also critical to the success of the application.
Ann, The key technology with the mobile robots I've seen is software enhancements and intelligent algorithms. Enhancements in vision systems, for example, provides the mechanism to visualize and ultimately "map" the factory environment but in the end the most difficult task is the mass of intelligent software required. It ranges from becoming an expert system (gathering information to make more informed decisions) to advanced databases for storing information. Lots of software
ChasChas, that's an interesting question you pose. But some of these newer robots will be functioning autonomously, like this one, i.e., not under direct human control. So if these are designed as soldiers, not as merely explorers, the ethical situation changes somewhat.
was my first encounter with what are called autonomous robots, and the one in this story is my second. Both made me wonder where else that idea is being used, and what different technologies make them possible, in particular, the navigation and map-making abilities. The industrial environment is certainly an obvious choice.
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