Machine Learning Meets Quantitative Planning: Enabling Self-Adaptation in Autonomous Robots

03/10/2019
by   Pooyan Jamshidi, et al.
0

Modern cyber-physical systems (e.g., robotics systems) are typically composed of physical and software components, the characteristics of which are likely to change over time. Assumptions about parts of the system made at design time may not hold at run time, especially when a system is deployed for long periods (e.g., over decades). Self-adaptation is designed to find reconfigurations of systems to handle such run-time inconsistencies. Planners can be used to find and enact optimal reconfigurations in such an evolving context. However, for systems that are highly configurable, such planning becomes intractable due to the size of the adaptation space. To overcome this challenge, in this paper we explore an approach that (a) uses machine learning to find Pareto-optimal configurations without needing to explore every configuration and (b) restricts the search space to such configurations to make planning tractable. We explore this in the context of robot missions that need to consider task timeliness and energy consumption. An independent evaluation shows that our approach results in high-quality adaptation plans in uncertain and adversarial environments.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 1

05/03/2019

Planning as Optimization: Dynamically Discovering Optimal Configurations for Runtime Situations

The large number of possible configurations of modern software-based sys...
01/18/2022

Lifelong Dynamic Optimization for Self-Adaptive Systems: Fact or Fiction?

When faced with changing environment, highly configurable software syste...
11/23/2021

Context-based navigation for ground mobile robot in a semi-structured indoor environment

There is a growing demand for mobile robots to operate in more variable ...
02/05/2021

Machine Learning-Based Automated Design Space Exploration for Autonomous Aerial Robots

Building domain-specific architectures for autonomous aerial robots is c...
05/11/2022

Towards Self-Adaptive Game Logic

Self-adaptive systems (SAS) can reconfigure at run time in response to c...
05/01/2022

Adversarial Plannning

Planning algorithms are used in computational systems to direct autonomo...
10/12/2018

SmartPM: Automatic Adaptation of Dynamic Processes at Run-Time

The research activity outlined in this PhD thesis is devoted to define a...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.