Aim of intense research in the field computational vision, dense 3D reconstruction achieves an important landmark with first methods running in real time with millimetric precision, using RGBD cameras and GPUs. However, these methods are not suitable for low computational resources. The goal of this work is to show a method of visual odometry using regular cameras, without using a GPU. The prop...

We address the problem of navigation in topometric maps created by using odometry data and visual loopclosure detection. Based on our previous work [6], we present an optimized version of our loop-closure detection algorithm that makes it possible to create consistent topo-metric maps in real-time while the robot is teleoperated. Using such a map, the proposed navigation algorithm performs qual...

The related fields of mobile robotics and ground vehicle localization lack a linearized theory of odometry error propagation. By contrast, the equivalent Schuler dynamics which apply to inertial guidance have been known and exploited for decades. In this paper, the general solution of linearized propagation dynamics of both systematic and random errors for vehicle odometry is developed and vali...

The improvement of odometry systems in collective robotics remains an important challenge for several applications. Social odometry is an online social dynamics which confers the robots the possibility to learn from the others. Robots neither share any movement constraint nor access to centralized information. Each robot has an estimate of its own location and an associated confidence level tha...

Visual odometry estimates a robot’s ego-motion with cameras installed on itself. With the advantages brought by camera being a sensor, visual odometry has been widely adopted in robotics and navigation fields. Drift (or error accumulation) from relative motion concatenation is an intrinsic problem of visual odometry in long-range navigation, as visual odometry is a sensor based on relative meas...

The mobile robots that are moving in partially known environments have a low availability, the mean time between failures being around 17.5 hours. From the total number of failures, 25% are localization failures caused mainly by odometry errors. Without a proper odometry error correction procedure, a wheeled mobile robot is not able to determine correctly its position and therefore it is lost. ...

Aggregation is a useful building block behaviour that can allow a swarm of robots to interact with each other or a user more easily. Previous work on swarm robot aggregation has assumed that the capabilities of individual robots are quite limited. We test whether incorporating odometry as an additional capability is helpful and make the argument that odometry is both realizable and biologically...

We address the problem of simultaneous localization and mapping (SLAM) by combining visual loop-closure detection with metrical information given by a robot odometry. The proposed algorithm extends a purely appearance-based loopclosure detection method based on bags of visual words [1] which is able to detect when the robot has returned back to a previously visited place. An efficient optimizat...

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