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We study the problem of objects search in clutter. In cluttered environments, partial occlusion among objects prevents vision systems from correctly recognizing objects. Hence, the agent needs to move objects around to gather information, which helps reduce uncertainty in perception. At the same time, the agent needs to minimize the efforts of moving objects to reduce the time required to complete...
In order to fully exploit the capabilities of a robotic systems, it is necessary to consider the limitations and errors of actuators and sensors already during the motion planning phase. In this paper, a framework for path planning is introduced, that uses heuristic search to build up a search graph in belief space, an extension to the deterministic state space considering the uncertainty associated...
This paper presents an active perception planning module embedded in a distributed functional cognitive architecture for complex environments. It discusses the functional module integration over the wish list concept, enabling distributed planning, reasoning and decision actions. Further the perception planning approach is depicted along with its components: the probabilistic framework for scene modeling,...
In military scenarios, agents (i.e., troops of soldiers, convoys, and unmanned vehicles) may often have to traverse environments with only a limited intelligence about the locations of adversaries. We study a particular instance of this problem that we refer to as path clearance problem.This article presents a survey of our work on scalable and suitable for real-time use approaches to solving the...
Safety is an important issue of driverless car. Yet, most current approaches fail to ensure safety even in a fully informed situation. In this paper we discuss how the safety criteria apply when the robot uses its on board sensors to evolve in an environment populated with static and moving obstacles. The sensors can only provide a partial and uncertain knowledge of the surroundings. We show that...
Knowledge of the driving environment is essential for robotic vehicles to comply with traffic rules while autonomously traversing intersections. However, due to limited sensing coverage and continuous changes in driving conditions, rigidly-mounted sensors may not guarantee coverage of all regions of interest, all the time. Unobserved regions around intersections increase uncertainty in driving conditions...
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