6 accepted papers
This paper presents a novel tightly coupled Filter-based monocular visual-inertial-wheel odometry (VIWO) system for ground robots, designed to deliver accurate and robust localization in long-term complex outdoor navigation scenarios. As an external sensor, the camera enhances localization performan
This paper describes autonomous landing of an unmanned aircraft system on a moving platform using vision and deep reinforcement learning. Landing on the moving platform offers several benefits such as more mission flexibility and reduced flight time. In particular, the end-to-end vision approach (i.
This paper proposes a deep reinforcement learning method for mobile sensors to estimate the properties of the source of the hazardous gas release. The problem of estimating the properties of the released gas is generally termed as the source term estimation (STE) problem. Since the sensor measuremen
This letter presents the trajectory planning of small unmanned aerial vehicles (UAVs) for a communication relay mission in an urban environment. In particular, we focus on predicting the communication strength between air and ground nodes accuratelyto allow relay UAVs to maximize the communication p
This paper presents experiments to assess the plume mapping performance of autonomous robots. The paper compares several mapping algorithms including Gaussian Process regression, Neural networks and polynomial and piecewise linear interpolation. The methods are compared in Monte Carlo simulations us…
This paper proposes the use of a learning approach to predict air-to-ground (A2G) communication strength in support of the communication relay mission using UAVs in an urban environment. To plan an efficient relay trajectory, A2G communication link quality needs to be predicted between the UAV and g…