Greg Kogut

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.

Towards a Warfighter's Associate: Eliminating the Operator Control Unit

In addition to the challenges of equipping a mobile robot with the appropriate sensors, actuators, and processing electronics necessary to perform some useful function, there coexists the equally important challenge of effectively controlling the system’s desired actions. This need is particularly critical if the intent is to operate in conjunction with human forces in a military application, as any low-level distractions can seriously reduce a warfighter’s chances of survival in hostile environments. Historically there can be seen a definitive trend towards making the robot smarter in order to reduce the control burden on the operator, and while much progress has been made in laboratory prototypes, all equipment deployed in theatre to date has been strictly teleoperated. There exists a definite tradeoff between the value added by the robot, in terms of how it contributes to the performance of the mission, and the loss of effectiveness associated with the operator control unit. From a command-and-control perspective, the ultimate goal would be to eliminate the need for a separate robot controller altogether, since it represents an unwanted burden and potential liability from the operator’s perspective. This paper introduces the long-term concept of a supervised autonomous Warfighter’s Associate, which employs a natural-language interface for communication with (and oversight by) its human counterpart. More realistic near-term solutions to achieve intermediate success are then presented, along with actual results to date. The primary application discussed is military, but the concept also applies to law enforcement, space exploration, and search-and-rescue scenarios.

Transitioning unmanned ground vehicle research technologies

The Technology Transfer project employs a spiral development process to enhance the functionality and autonomy of mobile systems in the Joint Robotics Program (JRP) Robotic Systems Pool (RSP). The approach is to harvest prior and on-going developments that address the technology needs identified by emergent in-theatre requirements and users of the RSP. The component technologies are evaluated on a transition platform to identify the best features of the different approaches, which are then integrated and optimized to work in harmony in a complete solution. The result is an enabling mechanism that continuously capitalizes on state-of-the-art results from the research environment to create a standardized solution that can be easily transitioned to ongoing development programs. This paper focuses on particular research areas, specifically collision avoidance, simultaneous localization and mapping (SLAM), and target-following, and describes the results of their combined integration and optimization over the past 12 months.

Using Advanced Computer Vision Algorithms on Small Mobile Robots

The Technology Transfer project employs a spiral development process to enhance the functionality and autonomy of mobile robot systems in the Joint Robotics Program (JRP) Robotic Systems Pool by converging existing component technologies onto a transition platform for optimization. An example of this approach is the implementation of advanced computer vision algorithms on small mobile robots. We demonstrate the implementation and testing of the following two algorithms useful on mobile robots: 1) object classification using a boosted Cascade of classifiers trained with the Adaboost training algorithm, and 2) human presence detection from a moving platform. Object classification is performed with an Adaboost training system developed at the University of California, San Diego (UCSD) Computer Vision Lab. This classification algorithm has been used to successfully detect the license plates of automobiles in motion in real-time. While working towards a solution to increase the robustness of this system to perform generic object recognition, this paper demonstrates an extension to this application by detecting soda cans in a cluttered indoor environment. The human presence detection from a moving platform system uses a data fusion algorithm which combines results from a scanning laser and a thermal imager. The system is able to detect the presence of humans while both the humans and the robot are moving simultaneously. In both systems, the two aforementioned algorithms were implemented on embedded hardware and optimized for use in real-time. Test results are shown for a variety of environments.

Target detection, acquisition, and prosecution from an unmanned ground vehicle

Weapon payloads are becoming increasingly important components of unmanned ground vehicles (UGVs). However weapon payloads are extremely difficult to teleoperate. This paper explores the issues involved with automating several aspects of the operations of a weapon payload. These operations include target detection, acquisition, and tracking. Various approaches to these issues are discussed, and the development and results from two different working prototype systems developed at Space and Naval Warfare Systems Center, San Diego (SSC San Diego) are presented. One approach employs a motion-based scheme for target identification, while the second employs an appearance based scheme. Target selection, arming and firing remain teleoperated in both systems.