Using Iterative Repair to Improve the Responsiveness of Planning and Scheduling
The majority of planning and scheduling research has focused on batch-oriented models of planning.
Engineering topics
Publications and source records attributed to Rabideau, G..
The majority of planning and scheduling research has focused on batch-oriented models of planning.
We describe a methodology for representing and optimizing user preferences on plans.
This paper will discuss a proof-of-concept prototype for automatic generation of validated rover command sequences from high-level science and engineering activities.
This paper describes a dynamic planning system for coordinating multiple rovers in collecting planetary surface data.
This paper describes the Automated Scheduling and Planning Environment (ASPEN). ASPEN encodes complex spacecraft knowledge of operability constraints, flight rules, spacecraft hardware, science experiments and operations procedures to allow for automated generation of low level spacecraft sequences. Using a technique called iterative repair, ASPEN classifies constraint violations (i.e., conflicts) and attempts to repair each by performing a planning or scheduling operation. It must reason about which conflict to resolve first and what repair method to try for the given conflict. ASPEN is currently being utilized in the development of automated planner/scheduler systems for several spacecraft, including the UFO-1 naval communications satellite and the Citizen Explorer (CX1) satellite, as well as for planetary rover operations and antenna ground systems automation. This paper focuses on the algorithm and search strategies employed by ASPEN to resolve spacecraft operations constraints, as well as the data structures for representing these constraints.
This paper describes and evaluates three methods for coordinating mutiple agents.
This paper describes a dynamic planning system for coordinating multiple rovers in collecting planetary surface data.
An autonomous spacecraft must balance long-term and short-term considerations. It must perform purposeful activities that ensure long-term science and engineering goals are achieved and ensure that it maintains resource margins.
This paper describes an integrated system for coordinating multiple rover behavior with the overall goal of collecting planetary surface data.
This paper describes the Automated Scheduling and Planning Environment (ASPEN). ASPEN encodes complex spacecraft knowledge of operability constraints, flight rules, spacecraft hardware, science experiments and operations procedures to allow for automated generation of low level spacecraft sequences.
The paper presents a rover execution architecture for controlling multiple, cooperating rovers. The overall goal of this architecture is to coordinate multiple rovers in performing complex tasks for planetary science.
Automated planning and scheduling, including automated path planning, has been integrated with an internet-based distributed operations system for planetary rover operations.
In this paper, we describe how rover command generation can be automated to help relieve some of the burden on human operators.
This paper describes an integrated planning and execution architecture that supports continuous modification and updating of a current working plan in light of changing operating context.
Automated planning and scheduling technology - we'll call it automated planning systems, for the sake of brevity-is applicable to a wide spectrum of spaceflight missions, from those with limited onboard computational capabilities, such as Lunar Prospector, to those with highly sophisticated software, such as Cassini.
This paper describes the DATA-CHASER Automated Planner/Scheduler (DCAPS) system which automated generation and repair of command sequences for the DATA-CHASER shuttle payload.
The Deep Space One (DS1) mission, scheduled to fly in 1998, will be the first NASA spacecraft to feature an on-board planner. The planner is part of an artificial intelligence based control architecture that comprises the planner/scheduler, a plan execution engine, and a model-based fault diagnosis and reconfiguration engine...This paper describes the on-board planning and scheduling component of the DS1 autonomy architecture.