Christopher P. Diehl

Distributed surveillance and reconnaissance using multiple autonomous ATVs: CyberScout

The objective of the CyberScout project is to develop an autonomous surveillance and reconnaissance system using a network of all-terrain vehicles. We focus on two facets of this system: 1) vision for surveillance and 2) autonomous navigation and dynamic path planning. In the area of vision-based surveillance, we have developed robust, efficient algorithms to detect, classify, and track moving objects of interest (person, people, or vehicle) with a static camera. Adaptation through feedback from the classifier and tracker allow the detector to use grayscale imagery, but perform as well as prior color-based detectors. We have extended the detector using scene mosaicing to detect and index moving objects when the camera is panning or tilting. The classification algorithm performs well with coarse inputs, has unparalleled rejection capabilities, and can flag novel moving objects. The tracking algorithm achieves highly accurate (96%) frame-to-frame correspondence for multiple moving objects in cluttered scenes by determining the discriminant relevance of object features. We have also developed a novel mission coordination architecture, CPAD (Checkpoint/Priority/Action Database), which performs path planning via checkpoint and dynamic priority assignment, using statistical estimates of the environments motion structure. The motion structure is used to make both preplanning and reactive behaviors more efficient by applying global context. This approach is more computationally efficient than centralized approaches and exploits robot cooperation in dynamic environments better than decoupled approaches.

Collaborative surveillance using both fixed and mobile unattended ground sensor platforms

We begin by considering current shortfalls with conventional surveillance systems and discuss the potential advantages of distributed, collaborative surveillance systems. Distributed surveillance systems offer the capability to monitor activity from multiple locations over time thereby increasing the likelihood of obtaining discriminating data necessary for interpretation of the activity. Yet the multiplicity of sensors magnifies the volumes of data that must be processed. We present our vision of a system which generates timely interpretations of activities in the scene automatically through the use of mechanisms for collaboration among sensing systems and efficient perception methods which complement the sensing paradigm. Then we review our recent efforts toward achieving this goal and present initial results.

Wireless RF distribution in buildings using heating and ventilation ducts

An alternative method of distributing RF in buildings is proposed in which the heating and ventilation ducts are used as wave guides. Because of the relatively low wave guide loss, this method may lead to more efficient RF distribution than possible with radiation through walls or the use of leaky coax. Further, the use of existing infrastructure could lead to a lower-cost system. Initial experimental results are presented that demonstrate duct-assisted propagation between nearby offices in a university building. An example method is described for obtaining efficient coupling between coax and 8″x12″ rectangular duct over the 902-928 MHz ISM band.

Recent advances in distributed collaborative surveillance

In Carnegie Mellon Universitys CyberScout project, we are developing mobile and stationary sentries capable of autonomous reconnaissance and surveillance. In this paper, we describe recent advances in the areas of efficient perception algorithms (detection, classification, and correspondence) and mission planning. In detection, we have achieved improved rejection of camera jitter and environmental variations (e.g., lighting, moving foliage) through multi-modal filtering, and we have implemented panoramic backgrounding through pseudo-real-time mosaicing. In classification, we present methods for discriminating between individual, groups of individuals, and vehicles, and between individuals with and without backpacks. In correspondence, we describe an accurate multi-hypothesis approach based on both motion and appearance. Finally, in mission planning, we describe mapbuilding using multiple sensory cues and a computationally efficient decentralized planner for multiple platforms.

Network of collaborating mobile and stationary sensors

In Carnegie Mellon Universitys CyberScout project, we are developing a network of mobile and stationary sentries capable of autonomous reconnaissance and surveillance. In this paper, we describe the cooperative perception algorithms and mission planning necessary to achieve this task, including sensor-to-sensor target handoff methods and an efficient decentralized path-planning algorithm. These methods are applied to a typical law enforcement application, a building stakeout scenario.