Event cameras that asynchronously output low-latency event streams provide great opportunities for state estimation under challenging situations. Despite event-based visual odometry having been extensively studied in recent years, most of them are based on the monocular, while few research stereo vision. In this letter, we present ESVIO, first visual-inertial odometry, which leverages complemen...

This letter presents benchmark tests of various visual(-inertial) odometry algorithms on NVIDIA Jetson platforms. The compared include mono and stereo, covering Visual Odometry (VO) Visual-Inertial (VIO): VINS-Mono, VINS-Fusion, Kimera, ALVIO, Stereo-MSCKF, ORB-SLAM2 ROVIO. As these methods are mainly used for unmanned aerial vehicles (UAVs), they must perform well in situations where the size ...

An enhanced odometry method coupled with an inertial navigation sensor is introduced for skid-steered vehicle positioning in outdoor environments. In the proposed scheme, robot positioning and attitude is estimated based on an experimentally derived kinematic model. Besides, a low-cost INS unit is used to improve the quality of the rotational velocity of the robot as it is obtained by different...

We propose an approach for autonomous task partitioning in swarms of foraging robots. Task partitioning is the process of decomposing tasks into sub-tasks. Task partitioning impacts tasks execution and associated costs. Our approach is characterized by the use of a cost function, mapping the size of sub-tasks to the overall task cost. The robots model the cost function and use the model to sele...

Evidence grids provide a uniform representation fo r fusing temporally and spatially distinct sensor readings. However, the use of evidence grids requires that the robot be localizeo! within its environment. Odometry errors typically accumulate over time, making localization estimates degrade, and introducing significant errors into evidence grads as they are built. W e have addressed this prob...