Direct perception of traversibility affordance on range images through learning on a mobile robot

Uğur, Emre
In this thesis, we studied how physical affordances of the environment, such as traversibility for a mobile robot, can be learned. In particular, we studied how the physical properties of the environment, as acquired from range images obtained from a 3D laser scanner mounted on a mobile robot platform, can specify the traversibility affordance. A physics based simulation environment is used during exploration trials, where the traversibility affordances and the relevant features for each behavior are learned through physical interactions with the environment. The prediction accuracy in perceiving the traversibility affordances of the world, which includes several spherical, cylindrical and box shaped objects, is found to be 94 percent. Furthermore, it is observed that the robot uses only 1.1 percent of extracted features while perceiving the affordances. This in turn saves the time 76.6 percent in scanning and 81percent in feature processing. The robot is later tested in a simulated cluttered environment, surrounded by walls. It is able to successfully traverse in the environment, by selecting its behaviors based on the affordances provided, and performing them. The robot was able to avoid from the box shaped objects, and push-roll the spherical ones without making any object detection. In the last set of experiments, the trained affordance-based behavior selection scheme is partially veried in the real world with the Kurt3D robot.


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This thesis studies how an autonomous robot can learn affordances from its interactions with the environment and use these affordances in planning. It is based on a new formalization of the concept which proposes that affordances are relations that pertain to the interactions of an agent with its environment. The robot interacts with environments containing different objects by executing its atomic actions and learns the different effects it can create, as well as the invariants of the environments that aff...
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Çelikkanat, Hande; Şahin, Erol; Department of Computer Engineering (2008)
In this thesis, we study how and to what extent a self-organized mobile robot flock can be guided by informing some of the robots within the flock about a preferred direction of motion. Specifically, we extend a flocking behavior that was shown to maneuver a swarm of mobile robots as a cohesive group in free space, avoiding obstacles. In its original form, this behavior does not have a preferred direction and the flock would wander aimlessly. In this study, we incorporate a preference for a goal direction i...
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Evolutionary methods are shown to be useful in developing behaviors in robotics. Interest in the use of evolution in swarm robotics is also on the rise. However, when one attempts to use artificial evolution to develop behaviors for a swarm robotic system, he is faced with decisions to be made regarding some parameters of fitness evaluations and of the genetic algorithm. In this thesis, aggregation behavior is chosen as a case, where performance and scalability of aggregation behaviors of perceptron control...
Human motion analysis via axis based representations
Erdem, Sezen; Tarı, Zehra Sibel; Department of Computer Engineering (2007)
Visual analysis of human motion is one of the active research areas in computer vision. The trend shifts from computing motion fields to understanding actions. In this thesis, an action coding scheme based on trajectories of the features calculated with respect to a part based coordinate system is presented. The part based coordinate system is formed using an axis based representation. The features are extracted from images segmented in the form of silhouettes. We present some preliminary experiments that d...
A simulation tool for mc6811
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Citation Formats
E. Uğur, “Direct perception of traversibility affordance on range images through learning on a mobile robot,” M.S. - Master of Science, Middle East Technical University, 2006.