Aaron Burmeister

Segway robotic mobility platform

The Segway Robotic Mobility Platform (RMP) is a new mobile robotic platform based on the self-balancing Segway Human Transporter (HT). The Segway RMP is faster, cheaper, and more agile than existing comparable platforms. It is also rugged, has a small footprint, a zero turning radius, and yet can carry a greater payload. The new geometry of the platform presents researchers with an opportunity to examine novel topics, including people-height sensing and actuation modalities. This paper describes the history and development of the platform, its characteristics, and a summary of current research projects involving the platform at various institutions across the United States.

Real-world validation of three tipover algorithms for mobile robots

Mobile robot tipover is a concern as it can create dangerous situations for operators and bystanders, cause collateral damage to the surrounding environment, and result in an aborted mission. Algorithms have been developed by others to assess the stability of the robot, and many of these algorithms have been demonstrated using simulated data. In order to verify that these algorithms accurately match real-world behavior, we have collected data of a mobile robot tipping over and then compared this data to the stability measures provided by three algorithms: Zero-Moment Point (ZMP), Force-Angle stability measure (FA), and Moment-Height Stability measure (MHS). A small mobile robot platform based on the iRobot PackBot drove a course including ramps and obstacles; an IMU and GPS provided inertial and positional data for the algorithms, and the actual tipover event is determined from video footage of the tests. The average normalized measure at tipover event initiation was found to be 0.665 for ZMP, −0.094 for FA, and 0.023 for MHS, where a value of 1 corresponds to resting stability. Standard deviations were 0.38, 0.84, and 0.67, respectively. The measures show a significant amount of noise, which is likely due to the vibrations caused by movement of the tracks and could be reduced by employing additional filtering during data collection. The preliminary real-world data validates these tipover algorithms as able to assess robot stability, and they can be used as part of a tipover avoidance system.

A Segway RMP-based robotic transport system

In the area of logistics, there currently is a capability gap between the one-ton Army robotic Multifunction Utility/Logistics and Equipment (MULE) vehicle and a soldier’s backpack. The Unmanned Systems Branch at Space and Naval Warfare Systems Center (SPAWAR Systems Center, or SSC), San Diego, with the assistance of a group of interns from nearby High Tech High School, has demonstrated enabling technologies for a solution that fills this gap. A small robotic transport system has been developed based on the Segway Robotic Mobility Platform (RMP). We have demonstrated teleoperated control of this robotic transport system, and conducted two demonstrations of autonomous behaviors. Both demonstrations involved a robotic transporter following a human leader. In the first demonstration, the transporter used a vision system running a continuously adaptive mean-shift filter to track and follow a human. In the second demonstration, the separation between leader and follower was significantly increased using Global Positioning System (GPS) information. The track of the human leader, with a GPS unit in his backpack, was sent wirelessly to the transporter, also equipped with a GPS unit. The robotic transporter traced the path of the human leader by following these GPS breadcrumbs. We have additionally demonstrated a robotic medical patient transport capability by using the Segway RMP to power a mock-up of the Life Support for Trauma and Transport (LSTAT) patient care platform, on a standard NATO litter carrier. This paper describes the development of our demonstration robotic transport system and the various experiments conducted.

The development of a UGV-mounted automated refueling system for VTOL UAVs

This paper describes the latest efforts to develop an Automated UAV Mission System (AUMS) for small vertical takeoff and landing (VTOL) unmanned air vehicles (UAVs). In certain applications such as force protection, perimeter security, and urban surveillance a VTOL UAV can provide far greater utility than fixed-wing UAVs or ground-based sensors. The VTOL UAV can operate much closer to an object of interest and can provide a hover-and-stare capability to keep its sensors trained on an object, while the fixed wing UAV would be forced into a higher altitude loitering pattern where its sensors would be subject to intermittent blockage by obstacles and terrain. The most significant disadvantage of a VTOL UAV when compared to a fixed-wing UAV is its reduced flight endurance. AUMS addresses this disadvantage by providing forward staging, refueling, and recovery capabilities for the VTOL UAV through a host unmanned ground vehicle (UGV), which serves as a launch/recovery platform and service station. The UGV has sufficient payload capacity to carry UAV fuel for multiple launch, recovery, and refuel iterations. The UGV also provides a highly mobile means of forward deploying a small UAV into hazardous areas unsafe for personnel, such as chemically or biologically contaminated areas. Teaming small UAVs with large UGVs can decrease risk to personnel and expand mission capabilities and effectiveness. There are numerous technical challenges being addressed by these development efforts. Among the challenges is the development and integration of a precision landing system compact and light enough to allow it to be mounted on a small VTOL UAV while providing repeatable landing accuracy to safely land on the AUMS. Another challenge is the design of a UGV-transportable, expandable, self-centering landing pad that contains hardware and safety devices for automatically refueling the UAV. A third challenge is making the design flexible enough to accommodate different types of VTOL UAVs, such as the AAI iSTAR ducted-fan vehicle and small helicopter UAVs. Finally, a common command-and-control architecture which supports the UAV, UGV, and AUMS must be developed and interfaced with these systems to allow fully autonomous collaborative behaviors. Funded by the Joint Robotics Program, AUMS is part of a joint effort with the Air Force Research Laboratory and the Army Missile Research Development and Engineering Command. The objective is to develop and demonstrate UGVUAV teaming concepts and work with the warfighter to ensure that future upgrades are focused on operational requirements. This paper describes the latest achievements in AUMS development and some of the military program and first responder situations that could benefit from this system.

Automated Launch, Recovery, and Refueling for Small Unmanned Aerial Vehicles

Small unmanned aerial vehicles (UAVs) are hindered by their limited payload and duration. Consequently, UAVs spend little time in their area of operation, returning frequently to base for refueling. The effective payload and duration of small UAVs is increased by moving the support base closer to the operating area; however this increases risk to personnel. Performing the refueling operations autonomously allows the support base to be located closer to the operating area without increasing risk to personnel. Engineers at SPAWAR Systems Center San Diego (SSC San Diego) are working to develop technologies for automated launch, recovery, refueling, rearming, and re-launching of small UAVs. These technologies are intended to provide forward-refueling capabilities by teaming small UAVs with large unmanned ground vehicles (UGVs). The UGVs have larger payload capacities so they can easily carry fuel for the UAVs in addition to their own fuel and mission payloads. This paper describes a prototype system that launched and recovered a remotely-piloted UAV from a UGV and performed automated refueling of a UAV mockup.

Evolution of a radio communication relay system

Providing long-distance non-line-of-sight control for unmanned ground robots has long been recognized as a problem, considering the nature of the required high-bandwidth radio links. In the early 2000s, the DARPA Mobile Autonomous Robot Software (MARS) program funded the Space and Naval Warfare Systems Center (SSC) Pacific to demonstrate a capability for autonomous mobile communication relaying on a number of Pioneer laboratory robots. This effort also resulted in the development of ad hoc networking radios and software that were later leveraged in the development of a more practical and logistically simpler system, the Automatically Deployed Communication Relays (ADCR). Funded by the Joint Ground Robotics Enterprise and internally by SSC Pacific, several generations of ADCR systems introduced increasingly more capable hardware and software for automatic maintenance of communication links through deployment of static relay nodes from mobile robots. This capability was finally tapped in 2010 to fulfill an urgent need from theater. 243 kits of ruggedized, robot-deployable communication relays were produced and sent to Afghanistan to extend the range of EOD and tactical ground robots in 2012. This paper provides a summary of the evolution of the radio relay technology at SSC Pacific, and then focuses on the latest two stages, the Manually-Deployed Communication Relays and the latest effort to automate the deployment of these ruggedized and fielded relay nodes.

Automatic Payload Deployment System

The ability to precisely emplace stand-alone payloads in hostile territory has long been on the wish list of US warfighters. This type of activity is one of the main functions of special operation forces, often conducted at great danger. Such risk can be mitigated by transitioning the manual placement of payloads over to an automated placement mechanism by the use of the Automatic Payload Deployment System (APDS). Based on the Automatically Deployed Communication Relays (ADCR) system, which provides non-line-of-sight operation for unmanned ground vehicles by automatically dropping radio relays when needed, the APDS takes this concept a step further and allows for the delivery of a mixed variety of payloads. For example, payloads equipped with a camera and gas sensor in addition to a radio repeater, can be deployed in support of rescue operations of trapped miners. Battlefield applications may include delivering food, ammunition, and medical supplies to the warfighter. Covert operations may require the unmanned emplacement of a network of sensors for human-presence detection, before undertaking the mission. The APDS is well suited for these tasks. Demonstrations have been conducted using an iRobot PackBot EOD in delivering a variety of payloads, for which the performance and results will be discussed in this paper.

Design and Experimental Validation of a Simple Controller for a Multi-Segment Magnetic Crawler Robot

A novel, multi-segmented magnetic crawler robot has been designed for ship hull inspection. In its simplest version, passive linkages that provide two degrees of relative motion connect front and rear driving modules, so the robot can twist and turn. This permits its navigation over surface discontinuities while maintaining its adhesion to the hull. During operation, the magnetic crawler receives forward and turning velocity commands from either a tele-operator or high-level, autonomous control computer. A low-level, embedded microcomputer handles the commands to the driving motors. This paper presents the development of a simple, low-level, leader-follower controller that permits the rear module to follow the front module. The kinematics and dynamics of the two-module magnetic crawler robot are described. The robot’s geometry, kinematic constraints and the user-commanded velocities are used to calculate the desired instantaneous center of rotation and the corresponding central-linkage angle necessary for the back module to follow the front module when turning. The commands to the rear driving motors are determined by applying PID control on the error between the desired and measured linkage angle position. The controller is designed and tested using Matlab Simulink. It is then implemented and tested on an early two-module magnetic crawler prototype robot. Results of the simulations and experimental validation of the controller design are presented.