Universal Navigation Algorithm Planning Platform for Unmanned Systems

R. Sell*, P. Leomar* *Department of Mechatronics, Tallinn University of Technology, Ehitajate tee 5, 19086 Tallinn,

Estonia

raivo.sell@ttu.ee, priit@eli.ee

Keywords: autonomous navigation, unmanned vehicle, robotics

Abstract. The paper deals with route planning and message exchange platform development for unmanned vehicle systems like Unmanned Ground Vehicle (UGV) and Unmanned Aerial Vehicle (UAV). Existing solutions for both types of vehicles are discussed and analyzed. Based on existing solution an unified concept is introduced. In this paper we present the study where the universal navigation algorithm planning platform is developed aiming to provide common platform for different unmanned mobile robotic systems. The platform is independent from the application and the target software. The navigation and action planning activity is brought to the abstract layer and specific interfaces are used to produce the target oriented code, describing two different test platforms are presented and co-operation scenarios.

Introduction

Unmanned mobile systems (UMS) like UGV and UAV have been getting a lot of focus in today’s world. Both types of vehicles are highly sophisticated robotic and mechatronic systems mainly used in military conflicts but lately have been also entered into civilian sector. Unmanned vehicles (UV) are driven manually, in autonomous- or semi-autonomous regime. They can be controlled remotely by the operator, for example demining robot in rescue operations, or ran by an on-board autonomous algorithm, for example surveillance unmanned plane or helicopter, detecting specific situation awareness. The autonomous regime needs the pre-defined algorithm which takes into account external sensor readings and internal calculations. In autonomous navigation the precise positioning and vehicle attitude are main input parameters obtained from the sensors. The common navigation scenario is to reach certain waypoint and fulfill assigned mission or task in that position. Today, from technical point of view, the navigation algorithm development is a device specific task and is usually equipped with specific software or coding environment for this purpose. This brings us to the main shortcoming of this kind of applications where every type of vehicle has its own system for algorithm development and action planning. The approach lacks of maturity in some cases, as the platform development is time and resource dependent; lacks of compatibility such as, systems used for UAVs do not comply with the systems used for UGVs. There is very limited number of systems available which deal mainly with co-operational action planning where several unmanned systems from different categories are involved. Our development is aimed to solve these issues and offer an open universal platform for common navigation and action planning. Two different unmanned systems are used for the experiments and result validation. The first test platform is UGV, developed in Tallinn University of Technology. Autonomous vehicle is a prototype for the security purpose and can be used to guard a territory bounded by GPS coordinates. Robot is shown in Fig.1 a. Second test platform is a UAV developed by the Estonian company. Initially, both systems had separately developed navigation planning systems but can now be integrated by using new solution. The paper also covers the co-operation issues of unmanned vehicles, namely UAV and UGV. The tasks and problems in this domain are pointed out and benefits of using common platform explained.

Solid State Phenomena Vol. 164 (2010) pp 405-410© (2010) Trans Tech Publications, Switzerlanddoi:10.4028/www.scientific.net/SSP.164.405

All rights reserved. No part of contents of this paper may be reproduced or transmitted in any form or by any means without the written permission of thepublisher: Trans Tech Publications Ltd, Switzerland, www.ttp.net. (ID: 193.40.245.168-11/05/10,15:50:22)

a b

Fig. 1. Test platforms: a - Unmanned Ground Vehicle, b - Unmanned Aerial Vehicle

Unmanned Vehicle �avigation

Unmanned aerial vehicle (UAV). In recent years unmanned systems and UAVs in particular, have become very popular, with estimates predicting a significant growth in the number of users. Nowadays different civilian applications like pollution monitoring, geophysical prospecting, disaster monitoring and coast card services utilize benefits offered by use of UAVs besides military applications. The widespread adopting of such devices has been until now delayed mostly by higher than acceptable accident rate in the context of manned aircraft. However, the situation is now being improved by the development of automated take-off, landing and navigation systems, which not only improve safety but also are able to eliminate the need for piloted operator. The phenomenal success of unmanned air vehicles during different operations is fostering a view that the days of the manned platform for intelligence, surveillance and monitoring duties are soon to be over. This booming progress can be attributed to the following reasons [1]: ● low cost compared to manned aircraft; ● low operating costs and a capability of operating by unprepared; ● rapid development of the most up-to-date information technologies; ● no risk of flight crew accidents. Currently more than 30 countries are developing and manufacturing up to 150 types of unmanned air vehicles. Furthermore, over 80 UAV types are in service of 55 world armies [2]. UAVs are developed and manufactured following many different design principles. Majority of UAVs are developed and manufactured by Aerospace industry in different countries. Many of those UAV systems are capable of autonomous flight at various levels. The military market plays an important role in the unmanned system domain by determining progress trends in and financing the cutting edge development. In the academic community a relevant interest in UAVs has also been raised, as the UAVs can be used as excellent research platforms for objectively testing maturing technologies, different actuators and sensors, driving and behavioral models etc. UAV programs range from the combat tested MQ-1 Predator to the NASA funded Aero Vironment Helios drone, which demonstrated about 40 hours of solar-powered flight attained by covering the upper surface of the wings with solar panels, thus providing long endurance [3]. Also the size and range of UAVs varies greatly, for instance the Pioneer at 14 feet long has an operational radius of 100 nm [5], while Global Hawk at 44 feet long has an operational radius of 13,500 nautical miles [4]. EADD’S Corporate Research Centre has built an MAV, weighing 520 g and measuring 44×44 cm, to demonstrate the potential of miniature technologies.

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Unmanned ground vehicle (UGV). Unmanned Ground Vehicles are similar in working principles except they are operating on the ground. There are many types of UGVs in worldwide, staring from tiny micro robot up to big military vehicles. Most well known UGVs are operating in military field especially in bomb disposal applications. However these vehicles are mostly man operated and do not have a lot of autonomity. In civilian market UGVs are mostly used in warehouses and in closed areas for routine tasks. In recent years the UGVs have entered into the service market and are now popular in house cleaning (e.g. iRobot vacuum cleaner and pool cleaner), lawn mower and other everyday tasks. During the last five years in Tallinn University of Technology (TUT) several mid-class UGVs have been developed. In this study the mobile robot “UKU”, a civilian mid-class robot is used as a test platform. UKU is a standard electrically powered four wheel robot. The robot can have different applications like cleaning the roads, serving the agricultural works to guarding the restricted areas etc. Modular structure grants the flexibility of defining the task. Nevertheless, whatever task is assigned to the robot the main navigation and obstacle avoidance is needed and therefore is built in as base algorithm. Robot has two types of operations: man operated or autonomous regime. In autonomous regime the algorithm consists of base functionality and task specific functionality. Base functionality is similar to most unmanned vehicles and can therefore be designed in more abstract level than just device specific level. In base route planning and waypoint action for different vehicles used a common system as well as common software platform can be applied. For UKU design the special development methodology is used already in conceptual design phase where new integrated approach is applied [6]. Taking into account our development activity in UGV field and co-operation with UAV developers in private sector the co-operation between vehicles and common navigation planning platform is very much needed.

Software Platform

Every unmanned mobile system has to have some kind of control system. Either pre-programmable or online programmable, it always has some kind of software platform to control or program the vehicle. So far every autopilot or control system developer has its own vehicle and software platform. In most cases, it is not possible to use independently the platform or software. There is no widely accepted software platform for UAV ground control stations. All autopilot producers have their own software solutions. The UAV applications also lack a common solution. Based on these issues the research started to develop the universal navigation planning platform for UAV and UGV systems. Ground control station software of UAV is most commonly divided into two main parts. Map window and controls panel. On the Fig. 2 the map window is at the left and control panel at the right. Map window is used for mission planning and online situation awareness whereas the control panel is for controlling the airplane and acquiring the sensors data and its parameters.

Route Planning Metamodel and Unified Platform Concept

Different aspects need to be taken into account, while planning autonomous navigation for unmanned vehicles. As an example for ground vehicle it is important to have good obstacle avoidance algorithm and object detection on the route whereas aerial vehicle needs to deal with wind and altitude. However many high level operational targets have similar structure and can therefore be unified for both type of vehicles. This benefits especially if we need to plan joint mission for the vehicles and if autonomy is required. In this study we have focused on the waypoint action defining and high level rout planning. The platform uses newly developed System Modeling Language (SysML) [7] for the activity planning. Special SysML profile is developed for the mobile robots [8], which provide common scenarios for faster development.

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Fig. 2. UAV map and control panel window Route planning metamodel defines the planning method and process of building autonomous navigation algorithm. Simplified metamodel is shown in Fig. 3. The main aspects of creating algorithm is setting waypoints, action selecting in this waypoint, action parameter definition, guard conditions of accomplishing task in the waypoint and message exchange.

Fig. 3. Simplified metamodel of autonomous navigation planning In every waypoint a certain task can be picked. If there is no suitable task in the database a new task can be dynamically defined according to the task definition rules. In total following common actions are defined in the system:

• border patrol • disaster monitoring • nuclear radiation probing or sampling • day/night reconnaissance • target positioning

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• field/area monitory As an example some vehicle specific tasks are listed:

• aerial photography • geophysical prospecting • artillery spotting • field damage and casualty assessment • atmosphere gas analyses • plot cleaning

These actions are defined in the system and if selected, custom parameters have to be assigned. Every functional action is defined as a certain chain of single actions by the SysML activity or state machine diagram. In the Fig. 4 the example scenario is shown where SysML with custom profile is used.

ObjectIdentification

ScanArea

Get_object_pattern[]object found?

true

false

Get_object(dist)

Get_object_params[]

target object?

true

false

Record detection

AlertTrack object

Sendstream

Operatorinterrupt

Objectlost

act target positioning

Fig. 4. Target positioning activity When the navigation scenario is defined the target specific source code is expected to be delivered, which can be uploaded directly to the onboard control computer. This requires target specific interfaces, especially if non-standard control system is used on the vehicle. The developed system uses latest technological and operational concepts, providing a solution to a wide range of requirements targeting flexibility and cost efficiency, which for a small country are considered as the most important factors. It is considered that the developed system can be operable standalone, or integrated into a comprehensive surveillance and collaborative system.

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Conclusions

This paper covers the status of the development activities in the field of making universal navigation algorithm planning platform for unmanned systems. Brief overview is given on two different unmanned systems used as test platforms. Targeting the universal applicability of the UAV and UGV route planning metamodel and unified platform concept is presented. The overview is given on the current achievements and main considerations are discussed. The efforts for improving the route planning and message exchange platform design for various civilian applications taken into focus and near future conceptual software design will be concluded. As the areal platform - UAV usually has better line of sight capabilities, it is better to use UAV as relay platform for message exchange with UGV and GCS (Ground Control Station). If the GCS is very close to UGV it is better to use GCS as the main message exchange unit. Both platforms can then communicate with GCS directly.

Acknowledgment

This research was supported by the Estonian Scientific Foundation grant ETF7542 and Estonian Ministry of Education and Research Project SF0140113Bs08.

References

[1] Information in: http://www.puav.com

[2] Information in: http://www.capitol.northgrum.com

[3] Unmanned Aerial Vehicles Roadmap, Office of the Secretary of Defense, (2002)

[4] P. Leomar, M. Tamre, T. Riibe, T. Vaher, T. Haggi: Optimal Design and Analysis of UAV Swan Fuselage. Solid State Phenomena, 113 : Mechatronic Systems and Materials, (2006), p. 91 - 96

[5] North Atlantic Treaty Organization, Applications, Concepts and Technologies for Future Tactical UAVs, Tallinn RTO Lecture Series

[6] R. Sell, E. Coatanea, F. Christophe: Important aspects of early design in mechatronic, 6th International Conference of DAAAM Baltic Industrial Engineering, Tallinn, (2008)

[7] System Modeling Language (SysML) Specification. Version 1.0 Draft. OMG document ad/2006-03-01, (2006)

[8] R. Sell: Model Based Mechatronic Systems Modeling Methodology In Conceptual Design Stage, PhD thesis, TUT Press, Tallinn, (2007)

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