Activity Planning for Assistive Robots Using Chance-Constrained Stochastic Programming

In this article, we present a framework for planning an activity to be executed with the support of a robotic navigation assistant. The two main components are the activity and the motion planner. The activity planner composes a sequence of abstract activities, chosen from a given set, to synthesize...

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Vydáno v:IEEE transactions on industrial informatics Ročník 17; číslo 6; s. 3950 - 3961
Hlavní autoři: Bevilacqua, Paolo, Frego, Marco, Palopoli, Luigi, Fontanelli, Daniele
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 01.06.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Activity planning
assistive robots
chance constrained optimization (Opt)
Constraints
Informatics
integer programming
Legged locomotion
motion planning
Optimization
Planning
Probabilistic logic
Service robots
Stochastic processes
Stochastic programming
ISSN:1551-3203, 1941-0050
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Shrnutí:In this article, we present a framework for planning an activity to be executed with the support of a robotic navigation assistant. The two main components are the activity and the motion planner. The activity planner composes a sequence of abstract activities, chosen from a given set, to synthesize a plan. Each activity is associated with a point of interest in the environment and with probabilistic parameters that depend on the plan, which are characterized by simulations in realistic scenarios. The low-level action to pass from an activity to the next is handled by the motion planner, which secures the physical feasibility of the chosen actions and their compatibility with the constraints posed by the user and the environment. Indeed, the final plan must respect the user constraints and optimise his/her satisfaction from the activity. We show a possible model for the problem as a chance constrained optimization along with an efficient technique to find high-quality solutions.
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ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2020.3012094