Numerical Efficiency of Inverse Simulation Methods Applied to a Wheeled Rover

Extending the navigational capability of planetary rovers is essential for increasing the scientific outputs from such exploratory missions. In this paper a navigation method based on Inverse Simulation is applied to a four wheel rover. The method calculates the required control inputs to achieve a desired, specified response. Here this is a desired trajectory defined as a series of waypoints. Inverse Simulation considers the complete system dynamics of the rover to calculate the control input using an iterative, numerical Newton - Raphson scheme. The paper provides an insight into the numerical parameters that affect the performance of the method. Also, the influence of varying the timestep and the convergence tolerance is examined in terms of the quality of the calculated control input and the resulting trajectory, as well as the execution time. From this analysis a set of parameters and recommendations to successfully apply Inverse Simulation to a rover is presented

Optimal path shape for range-only underwater target localization using a Wave Glider

Underwater localization using acoustic signals is one of the main components in a navigation system for an autonomous underwater vehicle (AUV) as a more accurate alternative to dead-reckoning techniques. Although different methods based on the idea of multiple beacons have been studied, other approaches use only one beacon, which reduces the system’s costs and deployment complexity. The inverse approach for single-beacon navigation is to use this method for target localization by an underwater or surface vehicle. In this paper, a method of range-only target localization using a Wave Glider is presented, for which simulations and sea tests have been conducted to determine optimal parameters to minimize acoustic energy use and search time, and to maximize location accuracy and precision. Finally, a field mission is presented, where a Benthic Rover (an autonomous seafloor vehicle) is localized and tracked using minimal human intervention. This mission shows, as an example, the power of using autonomous vehicles in collaboration for oceanographic research.Peer ReviewedPostprint (author's final draft

Adaptive and intelligent navigation of autonomous planetary rovers - A survey

The application of robotics and autonomous systems in space has increased dramatically. The ongoing Mars rover mission involving the Curiosity rover, along with the success of its predecessors, is a key milestone that showcases the existing capabilities of robotic technology. Nevertheless, there has still been a heavy reliance on human tele-operators to drive these systems. Reducing the reliance on human experts for navigational tasks on Mars remains a major challenge due to the harsh and complex nature of the Martian terrains. The development of a truly autonomous rover system with the capability to be effectively navigated in such environments requires intelligent and adaptive methods fitting for a system with limited resources. This paper surveys a representative selection of work applicable to autonomous planetary rover navigation, discussing some ongoing challenges and promising future research directions from the perspectives of the authors

Sensitivity analysis of a relative navigation solution for unmanned aerial vehicles in a GNSS-denied environment

Cooperative navigation between two or more unmanned aerial vehicles (UAVs) is an important enabling technology for problems such as military reconnaissance, disaster response, and search and rescue. In many of these situations Global Navigation Satellite Systems (GNSS), such as Global Positioning System (GPS), may be unreliable or unavailable due to structural impedance or malicious signal jamming. Therefore, the task of maintaining a reliable relative navigation solution without the use of GNSS is an important need for the aforementioned missions.;To meet this need, this thesis focuses on the relative navigation between two UAVs that are operating in a GNSS-denied environment. In particular, the design and sensitivity of a navigation algorithm are presented. The navigation algorithm presented consists of an Unscented Kalman filter that fuses multiple on-board sensors to estimate the relative pose between two UAVs. These sensors include: strap-down inertial measurement units, ultra-wideband ranging radios, strap-down tri-axial magnetometers, and downward facing cameras. Through the use of a Monte Carlo simulation study, the presented algorithm\u27s performance sensitivity to various sensor payload characteristics, flight dynamics, and initial condition errors is evaluated. Additionally, a research platform that will provide for a future experimental evaluation of the algorithm presented in this thesis has been integrated and tested as part of this work

Learning Ground Traversability from Simulations

Mobile ground robots operating on unstructured terrain must predict which areas of the environment they are able to pass in order to plan feasible paths. We address traversability estimation as a heightmap classification problem: we build a convolutional neural network that, given an image representing the heightmap of a terrain patch, predicts whether the robot will be able to traverse such patch from left to right. The classifier is trained for a specific robot model (wheeled, tracked, legged, snake-like) using simulation data on procedurally generated training terrains; the trained classifier can be applied to unseen large heightmaps to yield oriented traversability maps, and then plan traversable paths. We extensively evaluate the approach in simulation on six real-world elevation datasets, and run a real-robot validation in one indoor and one outdoor environment.Comment: Webpage: http://romarcg.xyz/traversability_estimation

Analysis and design of a capsule landing system and surface vehicle control system for Mars exploration

Problems related to an unmanned exploration of the planet Mars by means of an autonomous roving planetary vehicle are investigated. These problems include: design, construction and evaluation of the vehicle itself and its control and operating systems. More specifically, vehicle configuration, dynamics, control, propulsion, hazard detection systems, terrain sensing and modelling, obstacle detection concepts, path selection, decision-making systems, and chemical analyses of samples are studied. Emphasis is placed on development of a vehicle capable of gathering specimens and data for an Augmented Viking Mission or to provide the basis for a Sample Return Mission

ESMD Space Grant Faculty Project

No abstract availabl