In order for unmanned vehicles such as rovers, aerial vehicles and underwater devices to work in diverse environments and perform previously unknown complex tasks they need to move effectively in diverse terrains and work in cooperation. In order to keep them working properly, it demands these unpiloted conveyance to navigate safely in changing scenarios with unknown static and dynamic obstacles while performing different tasks.
Navigation of mobile robots is a broad topic covering a large spectrum of different technologies and applications. It draws on some
very ancient techniques, as well as some of the most advanced space science and engineering. Currently, two relatively modern
systems have been extensively studied. One is satellite based Global Positioning Systems (GPS) and the other is image based
Vision Positioning Systems, which have the common feature of being under continual development. Between the two, a large
scale of navigational requirements can be met. However, these and other techniques have important disadvantages. GPS for example,
cannot be used indoors, in underground facilities (e.g. mining operations), tunnels and in environments where GPS information is not
readily available. Robotsí motion strategies must rely on sensory information to compute the movements according to the unforeseen
For mobile robotics, lasers, sonars and radios are common media used as navigational beacons. GPS has been widely used in autonomous navigation systems as the navigation sensor replacing the inertial measurement unit, which has been conventionally favored as the primary navigation sensor. Other types of navigational systems employ artificial landmarks.
In order to cope with the many disadvantages of traditional robotic navigational techniques and enable teams of unmanned mobile robots to reach their target in a 3D environment effectively we are investigating a novel navigational 3D method using Intelligent Dynamic-Landmarks (IDL). The methodology is envisioned to improve the maneuvering of diverse types of unmanned vehicles (e.g., ground rovers and aerial drones) while getting rid of traditional navigational errors such as common sensor failures and the potential errors when using dead reckoning.
The methodologies under development have the ability to allow robots to effectively move (navigate) even under the presence of external and internal disturnances such as sensor failure (partial or total).
The focus of the 3D-NUVID project is to develop methodologies to enable teams of
unmanned vehicles (e.g., aerial, land rovers, underwater robots, amphibious systems, etc.) to navigate
effectively in 3D environments (i.e., land, air, sea or a combination) even under sensor failure.
Fig. 1: Basic Cooperative Navigation using IDLs.
Fig. 2: Basic Navigation Strategy using IDLs and Origami Graphs.
Contributions within this project are been made in the following areas:
For more information regarding the research activities that we conduct in this project please contact Dr. A. Ramirez-Serrano: email@example.com
Mobile manipulator under
This robot can use its arm to connect to
diverse structures (including its peers)
and form 2D & 3D flexible/rigid