Analyzing the effectiveness of rescheduling and Flexible Execution methods to address uncertainty in execution duration for a planetary rover

Agrawal, Jagriti; Chi, Wayne; Chien, Steve; Rabideau, Gregg; Gaines, Daniel M.; Kühn, Stephen

doi:10.1016/j.robot.2021.103758

Cited by 8 publications

(7 citation statements)

References 13 publications

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“…A ground version of the M2020 planning system, called Copilot, is used during the campaign implementation and tactical planning steps both to assist in plan generation and also to provide feedback on what may be executed. An explanation system, called Crosscheck ( 40 ), is used to explain operations constraints and planner behavior. Another ground tool called PLANSIM enables the operations team to use downlinked rover telemetry after execution to reconstruct all planner invocations during execution and determine which activities were executed when.…”

Section: Methodsmentioning

confidence: 99%

Autonomous robotics is driving Perseverance rover’s progress on Mars

et al. 2023

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NASA’s Perseverance rover uses robotic autonomy to achieve its mission goals on Mars. Its self-driving autonomous navigation system (AutoNav) has been used to evaluate 88% of the 17.7-kilometer distance traveled during its first Mars year of operation. Previously, the maximum total autonomous distance evaluated was 2.4 kilometers by the Opportunity rover during its 14-year lifetime. AutoNav has set multiple planetary rover records, including the greatest distance driven without human review (699.9 meters) and the greatest single-day drive distance (347.7 meters). The Autonomous Exploration for Gathering Increased Science (AEGIS) system analyzes wide-angle imagery onboard to autonomously select targets for observations by the SuperCam instrument, a multimode sensor suite capable of millimeter-scale geochemical and mineralogical analysis. AEGIS enables observations of scientifically interesting targets during or immediately after long drives without the need for ground communication. OnBoard Planner (OBP) is a scheduling capability planned for operational use in September 2023 that has the potential to reduce energy usage by up to 20% and complete drive and arm-contact science campaigns in 25% fewer days on Mars. This paper presents an overview of the AutoNav, AEGIS, and OBP capabilities used on Perseverance.

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Section: Methodsmentioning

confidence: 99%

Autonomous robotics is driving Perseverance rover’s progress on Mars

et al. 2023

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“…Flexible execution allows the system to handle less-severe unexpected events without incurring the cost of replanning. Previous NASA missions have made heavy use of flexible execution, such as the Mars 2020 Perseverance rover (Agrawal et al 2021a). Our implementation differs in focus, emphasizing responses to adverse events.…”

Section: Flexible Executionmentioning

confidence: 99%

“…The M2020 Perseverance rover also plans to fly an onboard planner (Rabideau and Benowitz 2017) to reduce lost productivity from following fixed time conservative plans (Gaines and et al 2016). Like the planning approach we propose in this paper, the M2020 planning architecture also relies on rescheduling and flexible execution (Agrawal et al 2021a), ground-based compilation (Chi et al 2019), heuristics (Chi, Chien, and Agrawal 2020), and very limited handling of planning contingencies (Agrawal et al 2021b). However, it uses a non-backtracking planner, which limits its ability to optimize plans and the M2020 flight software does not support utility discovery.…”

Section: Related Workmentioning

confidence: 99%

Analyzing the Efficacy of Flexible Execution, Replanning, and Plan Optimization for a Planetary Lander

Wang

Russino

Basich

et al. 2022

ICAPS

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Plan execution in unknown environments poses a number of challenges: uncertainty in domain modeling, stochasticity at execution time, and the presence of exogenous events. These challenges motivate an integrated approach to planning and execution that is able to respond intelligently to variation. We examine this problem in the context of the Europa Lander mission concept, and evaluate a planning and execution framework that responds to feedback and task failure using two techniques: flexible execution and replanning with plan optimization. We develop a theoretical framework to estimate gains from these techniques, and we compare these predictions to empirical results generated in simulation. These results indicate that an integrated approach to planning and execution leveraging flexible execution, replanning, and utility maximization shows significant promise for future tightly-constrained space missions that must address significant uncertainty.

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“…Since h(q, q) can be associated with unknown dynamics, acceptable control performance of (1) depends on efficient computing of h(q, q). Although algorithms based on the inverse dynamic method 2 , as well as corrective methods for systems with fast and slow dynamics 3 , have been widely used to solve this problem, the work reported here, likewise in [55], considers that E 1 (θ) Z 3 (q)h(q, q) and E 2 (θ) G 3 (q)h(q, q) admit a polytopic representation.…”

Section: Parameter Varying and Recursive Polytope Dcsvmentioning

confidence: 99%

“…being X d ∈ SE(3) the target configuration of the endeffector. The matrices K p , K d , K i ≥ 0 are real and positive semidefinite matrices, the error configuration X must satisfy (3). The vector u ∈ IR 6 represents the target twist on task-space.…”

Section: Introductionmentioning

confidence: 99%

Control of Flexible Manipulator Robots Based on Dynamic Confined Space of Velocities: Dynamic Programming Approach

Peña Fernández

2022

Journal of Robotics and Control

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Linear Parameter Varying models-based Model Predictive Control (LPV-MPC) has stood out in manipulator robots because it presents well-rejection to dynamic uncertainties in flexible joints. However, it has become too weak when the MPC's optimization problem does not include kinematic constraints-based conditions. This paper uses dynamic confined space of velocities (DCSV) to include these conditions as a recursive polytopic constraint, guaranteeing optimal dependency on a simplex scheduling parameter. To this end, the local frame's velocities and torque/force preload of joints (related to violation of kinematic constraints) are associated with different time scale dynamics such that DCSV correlates them as a polytope. So, a classical LPV-MPC will be updated using a dynamic programming approach according to the DCSV-based polytope. As a result, one lemma about DCSV-based recursive polytope and a five-step procedure for two decoupled close-loop schemes with different time scales compose the LPV-MPC proposed method. Numerical validation shows that even for relevant flexibility situations, trajectory tracking performance is improved by tuning finite horizons and optimization problem constraints regarding DCSV's behavior.

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Analyzing the effectiveness of rescheduling and Flexible Execution methods to address uncertainty in execution duration for a planetary rover

Cited by 8 publications

References 13 publications

Autonomous robotics is driving Perseverance rover’s progress on Mars

Autonomous robotics is driving Perseverance rover’s progress on Mars

Analyzing the Efficacy of Flexible Execution, Replanning, and Plan Optimization for a Planetary Lander

Control of Flexible Manipulator Robots Based on Dynamic Confined Space of Velocities: Dynamic Programming Approach

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