A UGV’s ability to perceive its surroundings is critical to the achievement of autonomous mobility. The environment is too dynamic and map data too inaccurate to rely solely on a single navigation means, such as the global positioning system (GPS). The vehicle must be able to use data from onboard sensors to plan and follow a path through its environment, detecting and avoiding obstacles as required.

The goal of perception technology is to relate features in the sensor data to those features of the real world that are sufficient, both for the moment-to-moment control of the vehicle and for planning and replanning. Humans are so good at perception, the brain does it so effortlessly, that we tend to underestimate its difficulty. It is difficult, both because the perception process is not well understood and because the algorithms that have been shown to be useful in perception are computationally demanding.

The actions required by a UGV to move from A to B take place in a perceptually complex environment. An FCS UGV is likely to operate in any weather (rain, fog, snow), during day or night, in the presence of dust or other battlefield obscurants, and in conjunction with friendly forces opposed by an enemy. Perception system tasks are summarized in Table 4-2.

The UGV must be able to avoid positive obstacles such as rocks or trees (or indoors obstacles like furniture) and a negative obstacle such as a ditch. Water obstacles present special challenges; the UGV must avoid deep mud or swampy regions, where it could be immobilized, and must traverse slopes in a stable manner so that it will not turn over. The move from A to B can take place in different terrains and vegetation backgrounds (e.g., desert with rocks and cactus, woodland with varying canopy densities, scrub grassland, on a paved road with sharply defined edges, in an urban area), with different kinds and sizes of obstacles to avoid (rocks in the open, fallen trees masked by grass, collapsed masonry in a street), and in the presence of other features that have tactical significance (e.g., clumps of grass or bushes, tree lines, or ridge crests that could provide cover).

Each of these environments imposes its own set of demands on the perception system, modified additionally by such factors as level of illumination, visibility, and surrounding activity. In addition to obstacles it must detect such features as a road edge if the path is along a road, or features indicating a more easily traversed local trajectory if it is operating off-road. The perception system must be able to detect, classify, and locate a variety of natural and manmade features to confirm or refine the UGV’s internal estimate of its location (recognize land marks); to validate assumptions made by the global path planner prior to initiation of the

Front Matter (R1-R20)

Executive Summary (1-12)

1. Introduction (13-16)

2. Operational and Technical Requirements (17-29)

3. Review of Current UGV Efforts (30-41)

4. Autonomous Behavior Technologies (42-71)

5. Supporting Technologies (72-93)

6. Technology Integration (94-103)

7. Roadmaps to the Future (104-110)

8. Findings and Recommendations (111-115)

References (116-120)

Appendix A: Committee Member Biographical Sketches (121-124)

Appendix B: Meetings and Activities (125-126)

Appendix C: Autonomous Mobility (127-150)

Appendix D: Historical Perspective (151-160)