yeah, sounds to me like UAV type stuff has gone far faster than we've been generally told. behold...
Thursday
Command & Control
Area Dominance Munition
Ben Plenge, Air Force Research Laboratory/Munitions Directorate
The Air Force Research Laboratory, Munitions Directorate is developing the Area Dominance Munition or Dominator to suppress enemy activity in high threat areas with air delivered, network centric, persistent munitions capable of defeating the entire spectrum of ground mobile targets. With this concept, the Combatant Commander will have a weapon system to conduct effects based operations and a unique capability to shape the battlefield to meet his objectives. The enemy is effectively denied the ability to operate in his own territory through continued presence of this constellation of lethal, miniature, high endurance, multi-shot, persistent munitions capable of cooperatively striking high value targets. A constellation of Dominators pre-positioned over the enemy s battle space will negate the need for costly hypersonic solutions. Dominators are the lethal element of a system of systems which includes higher flying gateway vehicles for target tracking and cueing, expendable UAV refueling tankers, and air delivered microprobes. Key technology investments are being made in areas of advanced seeker, precision miniature warhead, propulsion, compressed carriage airframe, 2-way data link, in-flight autonomous refueling, anti-jam GPS/INS navigation, and cooperative attack logic. Details of the concept and key technologies will be discussed in the briefing.
Smart Wide Area Weapons For UAVs
Richard Sterchele, Lou Cataldo, Ben Smith, Freeda Ostis, Textron Systems
Weaponzing UAVs has become a major focus for the war fighter in recent conflicts. The majority of fielded UAV systems, some the size of manned aircraft, are large enough to carry a limited payload of precision guided munitions designed for attack helicopters and fighter aircraft.
With the trend in military UAVs toward smaller, lighter, and payload-constricted systems the ability to carry legacy munitions is almost eliminated, forcing the war fighter to look at other types of precision weapons. The advent of small munitions, some no larger than a coffee can, have the ability for a 350 lb UAV to defeat multiple armored threats in a single mission. These sensor fuzed family of munitions can provide the lethality required by the war fighter for families of small, medium and large UAVs. Newer alternate payload systems (weighing under 70 lbs) have the killing power of a 1000-pound cluster munition yet leave the battlefield void of hazardous duds.
It is these sensor fuzed and alternate payload munitions that are the future for weaponizing various sizes and classes of military UAVs.
A Common Unmanned Vehicle Communications System for the Littoral Combat Ship
Joseph Krajnak, Thomas Sides, Lee Tennison, Lloyd Decker, NAVSEA Dahlgren Division, Thomas Staley, SSC San Diego
The Littoral Combat Ship is the first platform that will require the integration of multiple Unmanned Vehicles to complete its mission. The Mine Warfare and Anti-Submarine Warfare Mission Packages will each be using two different Unmanned Surface Vehicles that must be controlled simultaneously. Due to space and RF limitations on the Sea Frame, the plan is to develop an integrated communication system known as the Multiple unmanned Vehicle Communications (MVC) system. This system consists of a shipboard Local Area Network (LAN), a networked radio system, and an associated Network Management Tool. MVC is being developed to provide a non-proprietary, IP-based, modular, scalable, secure, open architecture solution that can be used for all Unmanned Surface Vehicles deployed from LCS. Adherence to applicable standards has been maintained to ensure future modifications are easily incorporated. This paper provides an overview of the MVC design, lessons learned during the initial development efforts, and the current and future planned capabilities for MVC.
Randomized Planning for Multi-agent Teams
Dave Ferguson, Anthony Stentz, Carnegie Mellon University
We present a randomized planning algorithm capable of navigating teams of agents through rugged outdoor terrain to desired goal locations. Our approach constructs a joint plan for the entire team, so that team constraints (such as line-of-sight connectivity) can be incorporated into the planning process. Our approach quickly constructs an initial solution then works on improving the quality of this solution as deliberation time is available. If new information is received by the robots as they navigate through the environment (e.g. a previously unknown obstacle is detected), our algorithm is able to efficiently repair its previous solution to reflect this new information. We present results from a series of different multirobot scenarios involving up to a dozen team members.
Risk-Aware Mixed-Initiative Dynamic Replanning (RMDR) Program Update
Margaret Nervegna, Dr. Michael Ricard, Draper Lab
The Navy envisions missions being executed by multiple, heterogeneous teams of unmanned air, surface, and undersea vehicles. To accomplish these missions, the team must autonomously replan cooperative activities associated with the team mission objectives and team operating constraints, including intermittent communications. The team s operator must interact with the team as an entity as well as with individual vehicles within the team.
As part of ONR s Intelligent Autonomy program, Draper Laboratory is developing such capability. The coastal reconnaissance and monitoring mission, a complex scenario that exercises many of the capabilities being developed, is used for demonstration purposes. Operators provide team-tasking (pre-mission and replanning) inputs, approve generated plans, retask the team, and provide in-stride target identification. Inputs include time constraints, risk values for regions (maximum allowable time on the surface, no-go regions, minimum reserves, time-out rules, etc.), and additional activity-specific tasking. For a reconnaissance activity, these include regions of interest, target classes to detect, and the value of gathering information (detection or identification) on the target classes.
RMDR is composed of 7 demonstrations, (6 in simulation, the 7th an in-water demonstration.) This presentation will present an overview of the RMDR system, results of the first four demonstrations, and plans for future demonstrations.
Complex Task Allocation and Execution for Teams of Multiple Autonomous Vehicles
Robert Zlot, Anthony Stentz, The Robotics Institute, Carnegie Mellon University
Teams of unmanned vehicles promise to deliver significant benefits for many complex application scenarios, including ground-based reconnaissance. Such missions are most naturally described by human operators as a set of abstract requirements both for model simplicity and due to the unknown and dynamic nature of the working environment. Given the physically distributed nature of these missions and the inherent risk and uncertainty involved, autonomous teams are ideal for efficiently parallelizing the workload and providing additional robustness. We describe a distributed coordination framework for efficiently distributing a set of complex tasks among a team of robots in which tasks are allocated to vehicles by using specialized auction protocols. Typically, auction-based allocation algorithms require a mission planner to decompose the mission into primitive tasks a priori. However, we show that such a preplanning approach is both less efficient and capable in dealing with uncertainty and dynamic conditions. We have therefore introduced task tree auctions in which participants can bid on tasks described at multiple levels of abstraction and, when appropriate, redecompose tasks higher up in the hierarchy. We demonstrate an ability to dynamically replan for complex tasks in a distributed fashion both in simulation and on a team of autonomous outdoor robots.
Using Real-time Vision to Control a Convoy of Semi-Autonomous Unmanned Vehicles
Dr. D. J. Lee, Jonathan Anderson, Beau Tippetts, Brigham Young University, Robert Schoenberger, Agris-Schoen Vision Systems, Inc.
This paper presents a control system that is capable of guiding a convoy of semi-autonomous or fully autonomous unmanned vehicles. The control system will be able to establish different modes of operation, including following the preceding vehicle, avoiding obstacles as they are detected, and following the route specified by the operators of the system. The control system makes heavy use of real-time target tracking to ensure that each vehicle will be able to follow the vehicle immediately ahead of it in the convoy and at the same time maintains a safe distance and avoids obstacles. The lead vehicle could either be controlled directly by a human operator or could be given the coordinates and map of the route that it is to follow. Field Programmable Gate Array (FPGA) technology is used to implement the vision algorithms to ensure that they will run at the camera frame rate. FPGA technology has advanced sufficiently that a hardcore processor can be integrated directly in to the FPGA chip to use a real-time operating system for communication and control tasks. This paper will describe the control system and demonstrate its potential using small toy trucks as the platform.
Small Unmanned Aircraft Systems Advanced Concept Technology Demonstration (SUAS ACTD)
Dan Bernard, U.S. Army Natick Soldier Center/United States Special Operations Command
The SUAS ACTD is a United States Special Operations Command (USSOCOM) sponsored program that starts in government fiscal year 2006 (FY06) and runs through FY 2010. In addition to USSOCOM, participants include the U.S. Army Natick Soldier Center, the United Sates Marine Corps and AeroVironment, Inc. The purpose of the program is to identify and address technology/capability gaps in SUAS systems that are carried by individual operators (man-packable systems) and is based on recent operational experience with the value and limitations of these systems. The initial program structure divides these capability gaps into five focus areas:
1) Command, Control, and Communications
2) Payload Integration
3) Targeting
4) Platforms
5) Training and Simulations.
A recent SUAS Operational User s Conference and an SUAS ACTD Technology Conference indicate that although the five focus areas remain valid, the area that will likely receive the most initial emphasis is Command, Control and Communications.
Legged Robot Motion with Explicit Stability Constraints: Theory and Application
Adam Rzepniewski, Ph.D., Greg Andrews, C.S. Draper Laboratory
Legged robots are known to have mobility advantages over wheeled and tracked ground robots. However, the stability necessary for successful traversal of difficult terrain is rarely explicitly considered when designing motion algorithms. Commonly, stability is a byproduct of walking routines. Learned gaits may be stable over the terrain on which the robot is trained, or stability may be ignored due to the robot configuration, e.g. six-legged robots that can walk in an alternating-tripod gait. The lack of explicit consideration of such an important factor can lead to task failure if the robot is placed in a new or stability-difficult situation such as traversal of a steep slope, or exposure to a sudden external stimulus. In this paper, an angle-based algorithm for real-time optimization of stability is applied to a four-legged robot, the Sony AIBO®. The experimental results show a significant advantage to having this auto-stabilizing routine. Next, the stability algorithm is integrated with a walk controller to dynamically alter walking gaits to adjust to difficult terrain. This ensures that gaits learned on flat terrain are not applied directly when traversing undulating or steeply-sloped ground. Again, the auto-stabilizing routine is shown to significantly increase the mobility of the legged robot.
Accurate Location Management for UGVs in the Urban Environment
Charles H. Woloszynski, Innovative Concepts, Steve Rounds, L3 Communications
The future of unmanned vehicles requires tightly coordinated actions, not just in missions but also as coordinated sensor systems. This requires highly precise sensor geo-location, even in difficult urban environments that block GPS signals. To address this, we introduce a new algorithm that computes geo-location information with partial information from multiple sources in a scalable, distributed method.
The algorithm is Decentralized Cooperative Navigation (DCN). It combines multiple navigation sensor outputs from members distributed across a network to compute accurate 3D location information. This technology has been demonstrated with integrated altimetry, inertial measurement units (IMUs), and GPS to provide accurate 3D navigation for every network member in non-urban environments.
For urban environments, an addition of robust ad-hoc communication networks and purpose-built ranging radios overcomes the remaining technical challenge of an accurate distributed ranging solution. This engine completes the DCN implementation issues for urban deployment; laying the groundwork for successful tightly-coordinated UGV operations.
This paper describes recent efforts and test results from demonstrations of prototype systems. The results validate a robust implementation for navigation of a multiple member network, wherein sparse navigation sensor data is integrated in a decentralized manner to allow accurate navigation of each member of the network.
Helikites for Lifting Persistent Radio-Relay for Unmanned Systems
SA Sandy Allsopp, ALLSOPP HELIKITES LIMITED
Direct radio contact with unmanned systems is always desirable however autonomous the vehicle. Helikites provide a simple, robust and very reliable method of providing over-the-horizon communications. Helikites are a newly patented type of aerostat. Helikites are the worlds only sucessful lighter-than-air kites. Wind that pushes normal aerostats down actually pushes Helikites upwards. So Helikites are dramatically smaller than other aerostats of the same performance and Helikites fly smoothly in far higher winds. Helikites are the easiest and least expensive method yet devised to place objects persistently into the air. They are excellent at providing radio-relay to unmanned systems and troops. The comparitively low cost of Helikites frees funds for more unmanned vehicles and so enhances capability.
Helikites are being assessed by the U.S. Air Force as a method of providing radio-relay for missiles at Eglin AF Base in Florida in the Helikite Elevated Platform - Transmission Relay (HEP-TR) Program. Sandia Laboratories are using Helikites to transmit emergency communications for Helikite Elevated Platform - Communications Relay (HEP-CR). Both programs run by Carolina Unmanned Vehicles.
Allsopp Helikites Ltd believe that Helikites are the simplest answer to the problem of providing communications to UGV's and USV's.
Demonstrated Benefits of a Modular Framework for Mission Management and Control of Unmanned Vehicles
Geoffrey Butler, Nigel Cox, Rex Helton, Robert McSwiggen, Robert Settle, Judi Taylor, BAE Systems
Principal Issues
As unmanned vehicles proliferate across the battlespace, their overall force effectiveness could be multiplied if they were able to act cooperatively towards common objectives while interacting with all echelons of manned forces. A common mission planning, management, and control system using an open system architecture, consistent user interfaces, shared data repositories, and standards-compliant interfaces is needed. Optimally, the system should allow near real time management and sharing/displaying of information pertaining to contingency planning and in-progress operations.
Conclusions
Through an innovative combination of legacy tools and emerging capabilities from the United States and coalition partners, we have realized a novel mission management system capable of coordinating the operations of multiple air, surface, and subsurface vehicles. Its architecture allows rapid prototyping, spiral development, testing, and fielding of capabilities with less risk of obsolescence and greater assurance of component compatibility. In addition, its web enabled, service oriented implementation, and distributed operations allow it to be used by various echelons within a deployed fighting force concurrently to improve force effectiveness. The prototype system has been reviewed for management effectiveness of both unmanned air and surface vehicles. This paper reviews the current system capabilities, addresses lessons learned, and discusses projected capabilities.
Multi-UAV, Collaborative Sensor Management For UAV Team Survivability
Craig Stoneking, Phil DiBona, Adria Hughes, Lockheed Martin Advanced Technology Laboratories
Collaboration among a team of unmanned sensor platforms can provide significant military operational advantages, through improved situation awareness. Recent work on the Survivability Planner Associate Rerouter (SPAR) program, sponsored by the Army Aviation Technology Directorate (AATD), as well as internally-funded research and development, has provided insights into the challenges related to managing collaborative sensing, in support of the survivability of a team comprising a manned aircraft and multiple sensor-bearing UAV's. The paper will discuss technical challenges related to multi-UAV, collaborative sensor management, including: sensor resource allocation, sensor platform positioning for collaborative sensing, and integration of collaborative sensing behavior into a comprehensive multi-uav control system. The paper will also discuss recent, ongoing, and planned investigations into approaches to addressing those challenges.
Passive Acoustic Non-Cooperative Collision Alert System (PANCAS) for UAV Sense and Avoid
Duane Cline, S teve Wilcox, SARA, Inc., Charles Ingalls , US Army Aeroflightdynamics Directorate
The proliferation of unmanned air vehicles (UAVs) designed to perform a wide range of missions has accelerated dramatically in recent years. Unmanned aircraft are currently limited to operation within predetermined Restricted Operating Zones (ROZs) to minimize the potential for airspace conflicts with other aircraft, which can limit the employment of assets to meet time critical needs in a dynamic operational environment. Despite procedural airspace control, there have been cases of small UAVs colliding with helicopters in Iraq. Larger UAVs are equipped with transponders to provide UAV position information to cooperative aircraft and air traffic control systems, but these systems cannot prevent collisions with non-cooperative aircraft.
SARA, Inc. is developing the Passive Acoustic Non-cooperative Collision Alert System (PANCAS) to alert UAV users to the presence of non-cooperative air traffic in real time. Proof of concept tests have demonstrated the ability to detect potential collisions with helicopters and general aviation aircraft at ranges sufficient ranges to allow a small UAV to make maneuvers to maintain safe airspace separation under a variety of approach scenarios. The proposed paper will present the results of the Phase I program and plans for on-going technology development, demonstration and implementation.
Unmanned Aerial Vehicles (UAV) in Net-Centric Warfare: Incorporating Link 16 and Cursor-on-Target
Lt Jeremy Tachau, USAF HQ XO Combat Support Office
Lessons learned from Operation Enduring Freedom and Operation Iraqi Freedom (OEF/OIF), exercises and other joint operations establish the requirement to integrate Unmanned Aerial Vehicles (UAVs) into the physical and digital battle space, and allow fighter aircraft to slew to the UAV sensor report. Technology (government owned software) exists that integrates the accurate Identification (ID) and location information of UAVs into the Multi-TDL (Tactical Data Links) Network (MTN) environment. This capability also provides digital UAV sensor cueing to fighter aircraft and Command and Control (C2) agencies.
Future Capabilities:
1. Develop CoT software so the UAV mission commander:
a. can initiate a J3.5 land track on a target of interest (could include marking friendly locations).
b. can provide amplifying information on the land tracks (UAV generated or existing J3.5s) to include; ID, activity, spec type, re-report frequency etc.
2. Provide the UAV mission commander with a tactical situation display of link-16 so he/she can de-conflict with other aircraft and receive threat warning (Surface to Air Missile (SAM)).
Development of the above capability is crucial for airspace deconfliction of UAVs with other aircraft and for collapsing the sensor-to-shooter window by incorporating machine-to-machine solutions for sharing sensor data.
Cooperative Control of UAVs for Search and Localization
Prof. Vijay Kumar, GRASP Laboratory, Ben Grocholsky, James Keller, George Pappas, University of Pennsylvania
Unmanned Aerial Vehicles (UAVs) can be used to cover large areas searching for targets. However, sensors on UAVs are typically limited in their accuracy of localization of targets on the ground. On the other hand, Unmanned Ground Vehicles can be deployed to accurately locate ground targets. They have the disadvantage of not being able to move rapidly and see through such obstacles as buildings or fences.
In this paper, we describe how we can exploit this synergy by creating a seamless network of UAVs and UGVs. We describe our experimental testbed of UAVs and UGVs, the framework and algorithms, and some results, focussing mainly on the control of UAVs.
from:
http://www.auvsi.org/symposium/2006/abstract6.cfm
2006!
so...
remember the story recently about how large numbers of UAV controllers were in particular under heavy PTSD due to the much larger amount of killing they do, and they watch it on live TV before during and after. Apparently it get's a little hard to deal with after a point. S'ok, I'm sure they'll have go-pills for that any minute now. Maybe a job for our old pal Propranolol...
"hey boss, how did my shift go last night?"
"just fine"
"did we kill any bad guys?"
"of course not, you know we're only recon"
===
so... if this is so world changing... are we near the end of any concept of 'illegal' resistance? if they've really made a 'quantum leap' in enforcement/surveillance tech?
