A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Wireless Communications
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Probabilistic Robotics (Intelligent Robotics and Autonomous Agents)
Probabilistic Robotics (Intelligent Robotics and Autonomous Agents)
Self-organization in Autonomous Sensor and Actuator Networks
Self-organization in Autonomous Sensor and Actuator Networks
Toward humanoid manipulation in human-centred environments
Robotics and Autonomous Systems
Robotics and Autonomous Systems
Experimental comparison of RSSI-based localization algorithms for indoor wireless sensor networks
Proceedings of the workshop on Real-world wireless sensor networks
A visual odometry framework robust to motion blur
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Range-only SLAM with a mobile robot and a wireless sensor networks
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Hi-index | 0.00 |
This paper presents a robotic system that exploits Wireless Sensor Network (WSN) technologies for implementing an ambient intelligence scenario. We address the problems of robot object discovery, localization, and recognition in a fully distributed way. We propose to embed some memory, some computational power, and some communication capability in the objects, by attaching a WSN mote to each object.We called the union of an object and of a mote, a smart object. The robot does not have any information on the number nor on the kind of objects in the environment. The robot discovers the objects through the radio frequency communication provided by the WSN motes. The robot roughly locates the motes by performing a range-only SLAM algorithm based on the RSSI-range measurements. A more precise localization and recognition step is performed by processing images acquired by the camera installed on the robot and matching the descriptors extracted from these images with those transmitted by the motes. Experiments with eight smart objects in a cluttered office environment with many dummy objects are reported. The robot was able to correctly locate the motes, to navigate toward them and to correctly recognize the smart objects.