CARACaS multi-agent maritime autonomy for USVs in the Swarm II harbor patrol demonstration
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Sandoval, Michael↗
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CARACaS multi-agent maritime autonomy for unmanned surface vehicles in the Swarm II harbor patrol demonstration
This paper describes new autonomy technology that enabled a team of unmanned surface vehicles (USVs) to execute cooperative behaviors in the USV Swarm II harbor patrol demonstration and provides a description of autonomy performance in the event. The new developments extend the NASA Jet Propulsion Laboratory’s CARACaS (Control Architecture for Robotic Agent Command and Sensing) autonomy architecture, which pro- vides foundational software infrastructure, core executive functions, and several default robotic technology mod- ules. In Swarm II, CARACaS demonstrated higher levels of autonomy and more complex cooperation than previous on-water exercises, using full-sized vehicles and real-world sensing and communication. The core au- tonomous behaviors to support the harbor patrol scenario included Patrol, Track, Inspect, and Trail, providing the capability of finding all vessels entering the patrol area, keeping track of them, inspecting them to infer intent, and trailing suspect vessels. Significantly, CARACaS assumed responsibility for not only executing tasks safely and efficiently but also recognizing what tasks needed to be accomplished, given the current state of the world. Since the heterogeneous USV teams shared world model that evolved, such as due to (dis)appearance of vessels in the area or a change in health or availability of a USV, CARACaS replanned to generate and reallocate the new task list. Thus, human intervention was never required in the loop to task USVs during mission execution, though a supervisory role was supported in the autonomy system for mission monitoring and exception handling. Finally, CARACaS also ensured the USVs avoided hazards and obeyed the applicable rules of the road, using its local motion planning modules.
Sandoval, Michael↗
Mission Level Autonomy for USSV
On-water demonstration of a wide range of mission-proven, advanced technologies at TRL 5+ that provide a total integrated, modular approach to effectively address the majority of the key needs for full mission-level autonomous, cross-platform control of USV s. Wide baseline stereo system mounted on the ONR USSV was shown to be an effective sensing modality for tracking of dynamic contacts as a first step to automated retrieval operations. CASPER onboard planner/replanner successfully demonstrated realtime, on-water resource-based analysis for mission-level goal achievement and on-the-fly opportunistic replanning. Full mixed mode autonomy was demonstrated on-water with a seamless transition between operator over-ride and return to current mission plan. Autonomous cooperative operations for fixed asset protection and High Value Unit escort using 2 USVs (AMN1 & 14m RHIB) were demonstrated during Trident Warrior 2010 in JUN 2010
maritime autonomy↗
Intelligent Autonomy for Unmanned Surface and Underwater Vehicles
As the Autonomous Underwater Vehicle (AUV) and Autonomous Surface Vehicle (ASV) platforms mature in endurance and reliability, a natural evolution will occur towards longer, more remote autonomous missions. This evolution will require the development of key capabilities that allow these robotic systems to perform a high level of on-board decisionmaking, which would otherwise be performed by humanoperators. With more decision making capabilities, less a priori knowledge of the area of operations would be required, as these systems would be able to sense and adapt to changing environmental conditions, such as unknown topography, currents, obstructions, bays, harbors, islands, and river channels. Existing vehicle sensors would be dual-use; that is they would be utilized for the primary mission, which may be mapping or hydrographic reconnaissance; as well as for autonomous hazard avoidance, route planning, and bathymetric-based navigation. This paper describes a tightly integrated instantiation of an autonomous agent called CARACaS (Control Architecture for Robotic Agent Command and Sensing) developed at JPL (Jet Propulsion Laboratory) that was designed to address many of the issues for survivable ASV/AUV control and to provide adaptive mission capabilities. The results of some on-water tests with US Navy technology test platforms are also presented.
environmental sensing↗
Process Algebra Approach for Action Recognition in the Maritime Domain
The maritime environment poses a number of challenges for autonomous operation of surface boats. Among these challenges are the highly dynamic nature of the environment, the onboard sensing and reasoning requirements for obeying the navigational rules of the road, and the need for robust day/night hazard detection and avoidance. Development of full mission level autonomy entails addressing these challenges, coupled with inference of the tactical and strategic intent of possibly adversarial vehicles in the surrounding environment. This paper introduces PACIFIC (Process Algebra Capture of Intent From Information Content), an onboard system based on formal process algebras that is capable of extracting actions/activities from sensory inputs and reasoning within a mission context to ensure proper responses. PACIFIC is part of the Behavior Engine in CARACaS (Cognitive Architecture for Robotic Agent Command and Sensing), a system that is currently running on a number of U.S. Navy unmanned surface and underwater vehicles. Results from a series of experimental studies that demonstrate the effectiveness of the system are also presented.
process algebras↗