Qualitative navigation for mobile robots
Artificial Intelligence
Computing in Euclidean geometry
Computing in Euclidean geometry
Learning metric-topological maps for indoor mobile robot navigation
Artificial Intelligence
The spatial semantic hierarchy
Artificial Intelligence
Mars Rover Autonomous Navigation
Autonomous Robots
Coarse Qualitative Descriptions in Robot Navigation
Spatial Cognition II, Integrating Abstract Theories, Empirical Studies, Formal Methods, and Practical Applications
Schematic Maps for Robot Navigation
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COSIT 2001 Proceedings of the International Conference on Spatial Information Theory: Foundations of Geographic Information Science
Qualitative Spatial Reasoning: A Semi-quantitative Approach Using Fuzzy Logic
SSD '89 Proceedings of the First Symposium on Design and Implementation of Large Spatial Databases
Global localization and topological map-learning for robot navigation
ICSAB Proceedings of the seventh international conference on simulation of adaptive behavior on From animals to animats
IROS '95 Proceedings of the International Conference on Intelligent Robots and Systems-Volume 2 - Volume 2
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
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ICTAI '96 Proceedings of the 8th International Conference on Tools with Artificial Intelligence
Convex Optimization
Qualitative spatial reasoning about sketch maps
AI Magazine
Using a hand-drawn sketch to control a team of robots
Autonomous Robots
Sketch-based navigation for mobile robots using qualitative landmark states
Sketch-based navigation for mobile robots using qualitative landmark states
Walk the talk: connecting language, knowledge, and action in route instructions
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Factoring the Mapping Problem: Mobile Robot Map-building in the Hybrid Spatial Semantic Hierarchy
International Journal of Robotics Research
Qualitative Spatial Modelling of Human Route Instructions to Mobile Robots
ACHI '10 Proceedings of the 2010 Third International Conference on Advances in Computer-Human Interactions
Integrating grid-based and topological maps for mobile robot navigation
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Spatial language for human-robot dialogs
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Predicting Controller Capacity in Supervisory Control of Multiple UAVs
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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A method for controlling a mobile robot using qualitative inputs in the context of an approximate map, such as one sketched by a human, is presented. By defining a desired trajectory with respect to observable landmarks, human operators can send semi-autonomous robots into areas for which a true map is not available. Waypoint planning is formulated as a quadratic optimization problem which takes advantage of the probabilistic representation of the observed environment and the uncertain human input, resulting in robot trajectories in the true environment that are qualitatively similar to those provided by the human. This paper formally presents a methodology in which waypoints are extracted from a hand-drawn sketch, and obstacle avoidance is naturally accommodated through the addition of constraints in the optimization problem. A sensitivity analysis is performed to study how map distortions, sensor constraints, and a priori knowledge of the map orientation affect the performance of the planner. Lastly, a set of user studies is presented to demonstrate the robustness of the planner to different users' sketched maps and to illustrate the efficacy of such a method for mobile robot control.