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Agrawal, Jagriti

Publications and source records attributed to Agrawal, Jagriti.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Ground and Onboard Automated Scheduling for the Mars 2020 Rover Mission

The Mars 2020 Rover mission is using automated scheduling in two capacities. As of March 2021 a ground-based scheduler automatically schedules rover wake/sleep and preheats to support Mars 2020 daily operations. Included in the ground system is an explainable scheduling tool that allows users in-sight into the schedule developed by the automated scheduler. An onboard scheduler that will allow the rover autonomously better account for variations in execution is in development for use later in the mission.

Towey, Shannon↗
NASA NTRS2021

Ground-based Automated Scheduling for Operations of the Mars 2020 Rover Mission

The National Aeronautics and Space Administration’s (NASA) Mars 2020 Rover, named Perseverance, landed on the surface of Mars in Jezero Crater on February 18, 2021. Since the landing, the rover’s activities have been planned with the aid of a ground-based automated scheduling system called Copilot. Automated scheduling is very rare for planetary rover missions. Historically humans have created a schedule manually and ensured that the schedule satisfied all constraints. Higher levels of automation in the system allows science planners to produce schedules for the rover more quickly. In addition to scheduling user-provided activities, Copilot generates and schedules two types of support activities: sleep activities and heating activities. Some activities require the CPU to be on as they execute, so Copilot schedules wakeups and shutdowns of the CPU at the appropriate times. Some activities require areas of the rover to be heated before they can execute, and that heating must be maintained throughout the duration of the activity. Copilot schedules the preheat and maintenance heating activities for the user-provided activities that require them. To facilitate Copilot usage, the Crosscheck tool shows the science planners how Copilot constructed a schedule. For activities that fail to be scheduled, Crosscheck gives information on the constraints that the activity would have violated. This gives the users insight into how to change the input activities and constraints in order to achieve a schedule that satisfies their goals.

Towey, Shannon↗
NASA NTRS2020

Using Explainable Scheduling for the Mars 2020 Rover Mission

Understanding the reasoning behind the behavior of an auto- mated scheduling system is essential to ensure that it will be trusted and consequently used to its full capabilities in critical applications. In cases where a scheduler schedules activities in an invalid location, it is usually easy for the user to infer the missing constraint by inspecting the schedule with the in- valid activity to determine the missing constraint. If a sched- uler fails to schedule activities because constraints could not be satisfied, determining the cause can be more challenging. In such cases it is important to understand which constraints caused the activities to fail to be scheduled and how to al- ter constraints to achieve the desired schedule. In this pa- per, we describe such a scheduling system for NASA’s Mars 2020 Perseverance Rover, as well as Crosscheck, an explain- able scheduling tool that explains the scheduler behavior. The scheduling system and Crosscheck are the baseline for oper- ational use to schedule activities for the Mars 2020 rover. As we describe, the scheduler generates a schedule given a set of activities and their constraints and Crosscheck: (1) provides a visual representation of the generated schedule; (2) analyzes and explains why activities failed to schedule given the con- straints provided; and (3) provides guidance on potential con- straint relaxations to enable the activities to schedule in future scheduler runs.

Chien, Steve↗
NASA NTRS2020

Using a Model of Scheduler Runtime to Improve the Effectiveness of Scheduling Embedded in Execution

Scheduling often interacts with execution. When the scheduler is developing a schedule, real time (execution) proceeds. Usually a scheduler cannot modify portions of the schedule expected to start execution prior to the scheduler's expected completion. In deployed systems, often little effort is spent on predicting scheduler runtime and instead an extremely conservative, simple model is used, resulting in loss of performance as less of the schedule can be updated. We develop predictive model(s) of scheduler runtime and use these models to improve scheduler and execution performance. We present several models of scheduler runtime based on a scheduler being deployed onboard NASA's next Mars rover, the M2020 rover Perseverance. The models consider algorithmic complexity, characteristics of the input plan, and prior runtime data. First, we show how these still relatively unsophisticated models can more accurately predict scheduler runtime compared to the static conservative baseline being used for the actual M2020 onboard scheduler. Second, we show how the more accurate scheduler runtime models' tighter (shorter) runtime predictions enable better scheduler performance as measured by makespan and percentage of activities executed. Finally, we discuss a number of future steps to further advance this line of work.

Chi, Wayne↗
NASA NTRS2020

Robustness Computation of Dynamic Controllability in Probabilistic Temporal Networks with Ordinary Distributions

Most existing works in Probabilistic Simple Temporal Networks (PSTNs) base their frameworks on well-defined probability distributions. This paper addresses on PSTN Dynamic Controllability (DC) robustness measure, i.e. the execution success probability of a network under dynamic control.We consider PSTNs where the probability distributions of the contingent edges are ordinary distributed (e.g. non-parametric, non-symmetric). We introduce the concepts of dispatching protocol (DP) as well as DP-robustness, the probability of success under a predefined dynamic policy.We propose a fixed-parameter pseudo-polynomial time algorithm to compute the exact DP-robustness of any PSTN under \textit{NextFirst} protocol, and apply to various PSTN datasets, including the real case of planetary exploration in the context of the Mars 2020 rover, and propose an original structural analysis.

Saint-Guillain, Michael↗
NASA NTRS2020

Enabling Limited Resource-Bounded Disjunction in Scheduling

We describe three approaches to enabling a severely computationallylimited embedded scheduler to consider a smallnumber of alternative activities based on resource availability.We consider the case where the scheduler is so computationallylimited that it cannot backtrack search. The first twoapproaches precompile resource checks (called guards) thatonly enable selection of a preferred alternative activity if sufficientresources are estimated to be available to schedule theremaining activities. The third approach mimics backtrackingby invoking the scheduler multiple times with the alternativeactivities. We present an evaluation of these techniques onMars mission scenarios (called sol types) from NASA’s nextplanetary rover where these techniques are being evaluatedfor inclusion in an onboard scheduler.

Vaquero, Tiago↗