13 accepted papers
This paper presents a unified decision-making framework that integrates Hybrid Markov Decision Processes (HMDPs) with Model Predictive Control (MPC), augmented by velocity-dependent safety margins and a prediction-aware hysteresis mechanism. Both the ego and surrounding vehicles are modeled as HMDPs…
We propose PRED-MPPI, the first MPPI variant that seamlessly integrates real-time disturbance preview and adaptive discretization for quadrotor tracking control under significant model inaccuracies and time-varying disturbances. Unlike prior MPPI variants (e.g., mathcal{L}_1-MPPI, DA-MPPI), which as…
Unmanned Aerial Vehicles (UAVs) are gaining attention for inspections due to their improved safety, efficiency, and accuracy, alongside reduced costs and environmental risks. Visual servoing is crucial for autonomous UAV flight in GPS-degraded environments, guiding the UAV by minimizing errors betwe
In the gas source search and localisation problem, the use of autonomous robots is of increasing interest due to their deployment speed and lack of human interaction with hazardous materials. This letter presents an aerial robotic platform for performing source term estimation of an unknown chemical
This paper advocates the Gaussian belief propagation solver for factor graphs in the case of gas distribution mapping to support an olfactory sensing robot. The local message passing of belief propagation moves away from the standard Cholesky decomposition technique, which avoids solving the entire…
Deep learning on 3D point clouds has drawn much attention, due to its large variety of applications in intelligent perception for automated and robotic systems. Unlike structured 2D images, it is challenging to extract features and implement convolutional networks over these unordered points. Althou…
The lane change maneuver is one of the typical maneuvers in various driving situations. Therefore the automatic lane change function is one of the key functions for autonomous vehicles. Many researches have been conducted in this field. Most existing work focused on the solutions for the static envi…
Mobile robotic gas distribution mapping (GDM) is a useful tool for hazardous scene assessment where a quick and accurate representation of gas concentration levels is required throughout a staging area. However, research in robotic path planning for GDM has primarily focused on mapping in open space…
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…
A method was previously developed by this author to optimise the flight path of a fixed wing UAV performing aerial surveys of complex concave agricultural fields. This relies heavily on a flight time in wind prediction model as its cost function. This paper aims to validate this model by comparing f…
Ahstract- This paper presents a method to estimate the original location and the mass of an instantaneous release of hazardous material into the atmosphere. It is formulated as an inverse problem, where concentration observations from a mobile sensor are fused with meteorological information and a G…
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…