Real-time obstacle avoidance for manipulators and mobile robots
International Journal of Robotics Research
Information-based objective functions for active data selection
Neural Computation
Simultaneous Localization and Map-Building Using Active Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-Time Simultaneous Localisation and Mapping with a Single Camera
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Real-Time Localisation and Mapping with Wearable Active Vision
ISMAR '03 Proceedings of the 2nd IEEE/ACM International Symposium on Mixed and Augmented Reality
Environment Learning for Indoor Mobile Robots: A Stochastic State Estimation Approach to Simultaneous Localization and Map Building (Springer Tracts in Advanced Robotics)
Information-based compact pose SLAM
IEEE Transactions on Robotics
The Effects of Partial Observability When Building Fully Correlated Maps
IEEE Transactions on Robotics
A New Active Visual System for Humanoid Robots
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Estimating Object Proper Motion Using Optical Flow, Kinematics, and Depth Information
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Analyzing the effect of landmark vectors in homing navigation
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
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A method for evaluating, at video rate, the quality of actions for a single camera while mapping unknown indoor environments is presented. The strategy maximizes mutual information between measurements and states to help the camera avoid making ill-conditioned measurements that are appropriate to lack of depth in monocular vision systems. Our system prompts a user with the appropriate motion commands during 6-DOF visual simultaneous localization and mapping with a handheld camera. Additionally, the system has been ported to a mobile robotic platform, thus closing the control-estimation loop. To show the viability of the approach, simulations and experiments are presented for the unconstrained motion of a handheld camera and for the motion of a mobile robot with nonholonomic constraints. When combined with a path planner, the technique safely drives to a marked goal while, at the same time, producing an optimal estimated map.