Mobile robot navigation

About: Mobile robot navigation is a research topic. Over the lifetime, 14713 publications have been published within this topic receiving 263092 citations.

Tracking for following and passing persons

Abstract: This paper presents a multiple target tracking approach for following and passing persons in the context of human-robot interaction. The general purpose for the approach is the use in human augmented mapping. This concept is presented and it is described how navigation and person following are subsumed under it. Results from experiments under test conditions and from data collected during a user study are also provided.

GRAMMPS: a generalized mission planner for multiple mobile robots in unstructured environments

Abstract: For a system of cooperative mobile robots to be effective in real-world applications it must be able to efficiently execute a wide class of complex tasks in potentially unknown and unstructured environments. Previous research in multi-robot systems has either been limited to relatively structured domains or to small classes of feasible missions. This paper describes a field-capable system called GRAMMPS which addresses this problem by coupling a general-purpose interpreted grammar for task definition with dynamic planning techniques. GRAMMPS supports a general class of local navigation systems and heterogeneous groups of robots, providing optimal execution of missions given current world knowledge. Simulations illustrating the capabilities of this system are provided. Results showing successful runs of this system on two autonomous off-road vehicles are also given.

Data association for mobile robot navigation: a graph theoretic approach

Abstract: Data association is the process of relating features observed in the environment to features viewed previously or to features in a map. This paper presents a graph theoretic method that is applicable to data association problems where the features are observed via a batch process. Batch observations detect a set of features simultaneously or with sufficiently small temporal difference that, with motion compensation, the features can be represented with precise relative coordinates. This data association method is described in the context of two possible navigation applications: metric map building with simultaneous localisation, and topological map based localisation. Experimental results are presented using an indoor mobile robot with a 2D scanning laser sensor. Given two scans from different unknown locations, the features common to both scans are mapped to each other and the relative change in pose (position and orientation) of the vehicle between the two scans is obtained.

The Autonomous City Explorer: Towards Natural Human-Robot Interaction in Urban Environments

Abstract: 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. It finds its way by interacting with pedestrians in a natural and intuitive way and building a topological representation of its surroundings. In a recent experiment the robot managed to successfully travel a 1.5 km distance from the campus of the Technische Universitat Munchen to Marienplatz, the central square of Munich. This article describes the principles and system components for navigation in urban environments, information retrieval through natural human-robot interaction, the construction of a suitable semantic representation as well as results from the field experiment.