Real-time obstacle avoidance for manipulators and mobile robots
International Journal of Robotics Research
Estimating uncertain spatial relationships in robotics
Autonomous robot vehicles
Topological direction-giving and visual navigation in large environments
Artificial Intelligence - Special volume on computer vision
Learning metric-topological maps for indoor mobile robot navigation
Artificial Intelligence
Sequential Operations in Digital Picture Processing
Journal of the ACM (JACM)
Experiences with an interactive museum tour-guide robot
Artificial Intelligence - Special issue on applications of artificial intelligence
The spatial semantic hierarchy
Artificial Intelligence
Computer and Robot Vision
FastSLAM: a factored solution to the simultaneous localization and mapping problem
Eighteenth national conference on Artificial intelligence
Vitra guide: multimodal route descriptions for computer assisted vehicle navigation
IEA/AIE'93 Proceedings of the 6th international conference on Industrial and engineering applications of artificial intelligence and expert systems
IEEE Transactions on Robotics
Interpretation of Spatial Language in a Map Navigation Task
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Constructing the generalized local Voronoi diagram from laser range scanner data
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
A solution to the Path Planning problem using angle preprocessing
Robotics and Autonomous Systems
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Recent advances in simultaneous localization and mapping permit robots to autonomously explore enclosed environments and, subsequently, navigate to selected positions within them. But, for many tasks, it is more useful to immediately navigate to goals in unexplored environments, without a map. This is possible if a human director can describe the ideal route to the robot using grounded symbols that both parties can perceive directly. In this paper, a mobile robot is autonomously navigated to many locations in a cluttered laboratory environment by a variety of routes. A series of topological navigation instructions are provided in advance by the director, in a form that can be expressed verbally and translates easily to software representation. The instructions are based on the perception of spatial affordances available to the robot, namely nearby junctions and edges in a pruned Generalized Voronoi Diagram. The operator can generate the instructions by viewing or imagining the environment without any measurements. Only three to five instructions are needed to navigate anywhere in our laboratory. The instructions contain only topology. No spatial measurements or environmental data such as landmarks are provided to the robot.