We present a set of architectural concepts which address the needs for integrating high-level planning activities with lower-level reactive or participatory behaviors. Based on lessons learned from our experience with a hierarchical architecture for autonomous crosscountry navigation, we have come to recognize various pitfalls that may arise from the misuse of abstraction. Consequently, we have adopted a new approach which emphasizes the minimization of information loss both within and between system layers. This change in perspective has allowed us to greatly enhance the overall capabilities and performance of our system. I.

This paper describes the first cross-country map and sensorbased autonomous operation of a robotic vehicle. Experiments on the Autonomous Land Vehicle in natural terrain were performed. An overview of the software architecture used for this achievement is discussed, and details of the perception and planning techniques are presented. We describe two key experiments where the vehicle avoided known and unknown obstacles in its path.

A reasoning system to support the planning and control requirements of an autonomous land vehicle is described. This system is designed specifically to handle diverse terrain with maximal speed, efficacy, and versatility. The hierarchical architecture for this system is presented along with the detailed algorithms, heuristics, and planning methodologies for the component modules. The architecture is structured such that lower-level modules perform tasks requiring greatest immediacy, while higher-level modules perform tasks involving greater assimilation of sensor data, making use of large amounts of a priori knowledge. In describing the component modules of this system, specific techniques for mission planning, map-based route planning, local terrain navigation, and reflexive vehicle control are presented.These techniques have been demonstrated both in a detailed realtime simulation and on a small indoor robotic vehicle.

This paper describes a highly distributed fault-tolerant control system capable of compensating for deficiencies in system-level performance even when the cause of a fault cannot be explicitly identified. Developed for an autonomous underwater vehicle that must remain operational for several weeks without human intervention, this system must be capable of dealing with events that cannot be anticipated at design time. A unique aspect of this system is that it handles such events by attempting to "do whatever works" if it is unable to diagnose and correct specific faults. The software architecture used in this approach is applicable to a wide range of complex autonomous control applications.