We present a novel representation of dynamic scenes perceived by moving agents. This type of environments require constant updates of the map information that uses conventional geometric representations due to the changing relative position of dynamic object to the static scene. We show that this changed representation of the environment increases the robustness and accuracy in the perception of the scene and simplifies significantly the processing and complexity of the perception module. At the same time, the changed representation allows also a better prioritization of attention to the moving object around the robot that takes into account not the Euclidean distance but the time-to-interaction (TTI), which is the core contribution of this approach. We present the mathematical framework behind the pro-posed representation and show examples, how this framework simplifies and robustifies the processing in the perception modules of a moving agent.
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Spatiotemporal Representation of Dynamic Scences
Semantic Scholar · Computer Science · 2019
Abstract
We present a novel representation of dynamic scenes perceived by moving agents. This type of environments require constant updates of the map information that uses conventional geometric representations due to the changing relative position of dynamic object to the static scene. We show that this changed representation of the environment increases the robustness and accuracy in the perception of the scene and simplifies significantly the processing and complexity of the perception module. At the same time, the changed representation allows also a better prioritization of attention to the moving object around the robot that takes into account not the Euclidean distance but the time-to-interaction (TTI), which is the core contribution of this approach. We present the mathematical framework behind the pro-posed representation and show examples, how this framework simplifies and robustifies the processing in the perception modules of a moving agent.