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The ability to perceive a robot's local environment is one of the main challenges in the development of mobile ground robots. Here, we present a robust model-based approach for detection and tracking of road networks in rural terrain. To get a rich environment representation, we fuse the complementary data provided by a 3D LIDAR and an active camera platform into an accumulated, colored 3D elevation...
“Cooperative Cognitive Control for Autonomous Underwater Vehicles” (Co3AUVs) is Collaborative Project (STREP) funded by the European Commission (EC) under the Seventh Framework Programme (FP7), “Information and Communication technologies” (ICT) Challenge 2: “Cognitive Systems, Interaction, Robotics”. The aim of Co3AUVs is to develop, implement and test advanced cognitive systems for coordination and...
This video demonstrates the progress of the CityFlyer project. The goal of the project is to develop an autonomous quadrotor helicopter capable of autonomous flight in indoor and outdoor 3D environments such as hallways, stairwells, forests, caves and tunnels. Currently we are focused on developing 3D mapping and navigation capabilities for indoor environments. This video shows our 6 Degree of Freedom...
In the recent years, 3D tracking has gained attention due to the perforation of powerful computers and the increasing interest in tracking applications. One of the most common tracking algorithms used is the Kalman filter. Kalman filter is a linear estimator that is based on approximating system's dynamics using Gaussian probability distribution. In this paper, we provide a detailed evaluation of...
This paper presents a method for measuring 3D environment by a tracked vehicle robot using a laser range finder (LRF) with an arm-type movable unit. The unit is mounted on the robot and the LRF is installed at the end of the unit. This sensing system enables the sensor to change position and to face at a right angle to a variety of configuration. Because of the occlusion can be avoided by this mechanism,...
Fire brigades and special agencies are often demanded to operate for search and aid of human lives in extremely dangerous scenarios. It is very important to first verify the safety of the environment and to obtain remotely a clear image of the scenario inside buildings or underground spaces. Several studies have been addressing the possibility of using robotic tools to carry out safe operations. This...
Scan-matching is a technique that can be used for building accurate maps and estimating vehicle motion by comparing a sequence of point cloud measurements of the environment taken from a moving sensor. One challenge that arises in mapping applications where the sensor motion is fast relative to the measurement time is that scans become locally distorted and difficult to align. This problem is common...
When operating in partially-known environments, autonomous vehicles must constantly update their maps and plans based on new sensor information. Much focus has been placed on developing efficient incremental planning algorithms that are able to efficiently replan when the map and associated cost function changes. However, much less attention has been placed on efficiently updating the cost function...
We present a system for monocular simultaneous localization and mapping (mono-SLAM) relying solely on video input. Our algorithm makes it possible to precisely estimate the camera trajectory without relying on any motion model. The estimation is completely incremental: at a given time frame, only the current location is estimated while the previous camera positions are never modified. In particular,...
In this paper, we study the time-optimal trajectory planning of a sensor attached to an unmanned aerial vehicle (UAV) to provide complete 3-dimensional coverage with applications to urban environments with 2.5-dimensional features. The basic approach is to approximate the features of interest with a set of non planar coverage surfaces and to design a motion plan that guarantees the coverage surface...
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