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Path planning for robots typically consists of finding a path from a given start state to one or multiple given goal states. However, there are situations in which the pose of the goal state is not explicitly known, e.g. in sensor-based autonomous driving in unknown environments. This paper presents a path planner that is capable of planning feasible paths(More)
As mobile robotics is gradually moving towards a level of semantic environment understanding, robust 3D object recognition plays an increasingly important role. One of the most crucial prerequisites for object recognition is a set of fast algorithms for geometry segmentation and extraction, which in turn rely on surface normal vectors as a fundamental(More)
The Autonomous City Explorer (ACE) project combines research from autonomous outdoor navigation and human-robot interaction. The ACE robot is capable of navigating unknown urban environments without the use of GPS data or prior map knowledge and finds its way by interacting with pedestrians in a natural and intuitive way and building a topological(More)
In mobile robotics, the segmentation of range data is an important prerequisite to object recognition and environment understanding. This paper presents an algorithm for realtime segmentation of a continuous stream of incoming range data. The method is an extension of the previously developed RBNN algorithm and proceeds in two phases: Firstly, the normal(More)
Mapping and tracking in dynamic environments for autonomously-moving robots is still challenging, despite being essential tasks. They are often done separately using occupancy grids and established object tracking algorithms. In this work, an approach is presented that estimates a uniform, low-level, grid-based world model including dynamic and static(More)
In this work, a framework for motion prediction of vehicles and safety assessment of traffic scenes is presented. The developed framework can be used for driver assistant systems as well as for autonomous driving applications. In order to assess the safety of the future trajectories of the vehicle, these systems require a prediction of the future motion of(More)
— One of the greatest challenges nowadays in robotics is the advancement of robots from industrial tools to companions and helpers of humans, operating in natural, populated environments. In this respect, the Autonomous City Explorer (ACE) project aims to combine the research fields of autonomous mobile robot navigation and human robot interaction. A robot(More)
In robotics applications such as SLAM (Simultaneous Localization and Mapping), loop closure detection is an integral component required to build a consistent topological or metric map. This paper presents an appearance based loop closure detection mechanism titled `IBuILD' (Incremental bag of BInary words for Appearance based Loop closure Detection). The(More)
This paper presents a method for reasoning about the safety of traffic situations. More precisely, the problem of safety assessment for partial trajectories for vehicles is addressed. Therefore, the Inevitable Collision States (ICS) as well as its probabilistic generalization the Probabilistic Collision States (PCS) are used. Thereby, the assessment is(More)
— This paper implements a real-time hand gesture recognition algorithm based on the inexpensive Kinect sensor. The use of a depth sensor allows for complex 3D gestures where the system is robust to disturbing objects or persons in the background. A Haarlet-based hand gesture recognition system is implemented to detect hand gestures in any orientation, and(More)