Trajectory planning for unmanned surface vehicles operating under wave-induced motion uncertainty in dynamic environments:

We present a deliberative trajectory planning method to avoid collisions with traffic vessels. It also plans traversal across wavefields generated by these vessels and minimizes the risk of failure. Our method searches over a state-space consisting of pose and time. And, it produces collision-free and minimum-risk trajectory. It uses a lookup table to account for motion uncertainty and failure risk. We also present speed-up techniques to increase performance. Our wave-aware planner produces plans that (1) have shorter execution times and safer when compared to previously developed reactive planning schemes and (2) comply with user-defined wave-traversal constraints and Collision Regulations (COLREGs

Safety-Aware Optimal Attitude Pointing for Low-Thrust Satellites

In geostationary orbit, long eclipses and the seasonal variations in the direction and intensity of the solar input can cause damage to sensitive equipment during attitude maneuvers, which may inadvertently point the equipment towards the Sun. The requirement that transmitting and receiving antennae remain pointed towards the Earth creates further restrictions to pointing directions. The aim of the study is to construct a novel geometric and reinforcement-learning-based method to determine attitude guidance maneuvers that maintain the equipment in safe and operational orientations throughout an attitude maneuver. The attitude trajectory is computed numerically using the geometric framing of Pontryagin’s maximum principle applied to the vehicle kinematics using the global matrix Lie group representation on SO(3), and the angular velocities are shaped using free parameters. The values of these free parameters are determined by a reinforcement learning algorithm to avoid the forbidden areas while maintaining the pointing in operational areas (modeled as subsets of the two-sphere of all possible pointing directions of a particular axis). The method is applied to a model geosynchronous satellite and demonstrated in a simulation

Dynamic modelling and control of a portable USV for bathymetric survey

The dynamic modelling and path following control of a stand up paddle board based unmanned surface vessel, of the type appropriate for bathymetric survey applications, are presented. The dynamic model is based on a 3.35 m (11 foot) inflatable paddle board weighing 15.5 kg (including instrumentation and propulsion system). A super-twisting path following control system is designed to mitigate wind-induced disturbances anticipated to affect a vehicle in the field, and which are expected to be exacerbated by the vessel\u27s low draft, light weight and high windage area. The performance of the system is investigated using simulations of the vehicle following a lawn mower shaped path within an 80\ \mathrm{m}\times 80\ \mathrm{m} area. The proposed path following controller is shown to be robust to disturbances that have a magnitude of up to about a third of the total thrust available, and which change rapidly (wind gusts)

Conceptualization and Implementation of a Reconfigurable Unmanned Ground Vehicle for Emulated Agricultural Tasks

Small-to-medium sized systems able to perform multiple operations are a promising option for use in agricultural robotics. With this in mind, we present the conceptualization and implementation of a versatile and modular unmanned ground vehicle prototype, which is designed on top of a commercial wheeled mobile platform, in order to test and assess new devices, and motion planning and control algorithms for different Precision Agriculture applications. Considering monitoring, harvesting and spraying as target applications, the developed system utilizes different hardware modules, which are added on top of a mobile platform. Software modularity is realized using the Robot Operating System (ROS). Self- and ambient-awareness, including obstacle detection, are implemented at different levels. A novel extended Boundary Node Method is used for path planning and a modified Lookahead-based Line of Sight guidance algorithm is used for path following. A first experimental assessment of the system’s capabilities in an emulated orchard scenario is presented here. The results demonstrate good path-planning and path-following capabilities, including cases in which unknown obstacles are present