Application of Near Global Optimization Methods to Receding Horizon Control of Unmanned Ground Vehicles on 3D Unstructured Terrain
نویسندگان
چکیده
In this paper, we show the results of applying stochastic sampling methods such as Cross Entropy method and Sampling Based Differential Dynamic Programming method to path planning of Unmanned Ground Vehicles (UGV) on unstructured 3D terrains. We show the superiority of sampling algorithms to local optimization methods such as Gauss Newton optimization method through simulations.A high fidelity physics engine model has been used to provide sample trajectories which account for terrain effects such as roll over and tire slip.
منابع مشابه
Temporal Range Registration for Unmanned 2 Ground and Aerial Vehicles
8 Abstract. An iterative temporal registration algorithm is presented in this article for registering 9 3D range images obtained from unmanned ground and aerial vehicles traversing unstructured 10 environments. We are primarily motivated by the development of 3D registration algorithms to 11 overcome both the unavailability and unreliability of Global Positioning System (GPS) within 12 required...
متن کاملConnectivity Maintenance Based on Multiple Relay UAVs Selection Scheme in Cooperative Surveillance
For the purpose of remote command and situation awareness, multiple unmanned aerial vehicles (UAVs) cooperative surveillance with a ground station via multihop communications is presented in this paper. Considering limited communication capacities, a reliable UAV-to-UAV communication relay chain is dynamically established for connectivity maintenance and real-time surveillance information trans...
متن کاملPath Planning for Cooperative Sensing Using Unmanned Vehicles
This work explores online path-planning for unmanned vehicles performing cooperative sensing. Much existing work employs receding-horizon optimization, where an objective function is repeatedly optimized over some short lookahead length. The use of receding horizon optimization often results in adhoc methods for dealing with the problem of myopic lookahead, where no value is visible in an agent...
متن کاملA Hybrid Algorithm based on Deep Learning and Restricted Boltzmann Machine for Car Semantic Segmentation from Unmanned Aerial Vehicles (UAVs)-based Thermal Infrared Images
Nowadays, ground vehicle monitoring (GVM) is one of the areas of application in the intelligent traffic control system using image processing methods. In this context, the use of unmanned aerial vehicles based on thermal infrared (UAV-TIR) images is one of the optimal options for GVM due to the suitable spatial resolution, cost-effective and low volume of images. The methods that have been prop...
متن کاملTerrain traversability analysis methods for unmanned ground vehicles: A survey
Motion planning for unmanned ground vehicles (UGV) constitutes a domain of research where several disciplines meet, ranging from artificial intelligence and machine learning to robot perception and computer vision. In view of the plurality of related applications such as planetary exploration, search and rescue, agriculture, mining and off-road exploration, the aim of the present survey is to r...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2010