mlsanityData to 7 Oct 2026

Behavior Trees in Robot Control Systems

arXiv 2203.13083 ↗First posted 24 Mar 2022cs.RO cs.AIcited by 13

Not on the map. Why?

Abstract (arXiv)

In this paper we will give a control theoretic perspective on the research area of behavior trees in robotics. The key idea underlying behavior trees is to make use of modularity, hierarchies and feedback, in order to handle the complexity of a versatile robot control system. Modularity is a well-known tool to handle software complexity by enabling development, debugging and extension of separate modules without having detailed knowledge of the entire system. A hierarchy of such modules is natural, since robot tasks can often be decomposed into a hierarchy of sub-tasks. Finally, feedback control is a fundamental tool for handling uncertainties and disturbances in any low level control system, but in order to enable feedback control on the higher level, where one module decides what submodule to execute, information regarding progress and applicability of each submodule needs to be shared in the module interfaces. We will describe how these three concepts come to use in theoretical analysis, practical design, as well as extensions and combinations with other ideas from control theory and robotics.

Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). Builds on 19 of its 65 references that are in the map. First posted on arXiv 24 Mar 2022.

Builds on

19 of 65 references.

References · 19

  1. 2019Control Barrier Functions: Theory and Applicationscited by 332
  2. 2017Behavior Trees in Robotics and AI: An Introductioncited by 105
  3. 2020A Survey of Behavior Trees in Robotics and AIcited by 53
  4. 2016Towards Blended Reactive Planning and Acting using Behavior Treescited by 20
  5. 2019Representing Robot Task Plans as Robust Logical-Dynamical Systemscited by 15
  6. 2015Learning of Behavior Trees for Autonomous Agentscited by 14
  7. 2020On modularity in reactive control architectures, with an application to formal verificationcited by 11
  8. 2021Combining Planning and Learning of Behavior Trees for Robotic Assemblycited by 9
  9. 2021On the Implementation of Behavior Trees in Roboticscited by 9
  10. 2015A Framework for Constrained and Adaptive Behavior-Based Agentscited by 8
  11. 2020Learning Behavior Trees with Genetic Programming in Unpredictable Environmentscited by 7
  12. 2018Adding Neural Network Controllers to Behavior Trees without Destroying Performance Guaranteescited by 6
7 more
  1. 2021An expressiveness hierarchy of Behavior Trees and related architecturescited by 6
  2. 2021Optimized Execution of PDDL Plans using Behavior Treescited by 4
  3. 2020Combining Control Barrier Functions and Behavior Trees for Multi-Agent Underwater Coverage Missionscited by 3
  4. 2021Continuous-Time Behavior Trees as Discontinuous Dynamical Systemscited by 3
  5. 2019Automatic difficulty management and testing in games using a framework based on behavior trees and genetic algorithmscited by 2
  6. 2016Simulation Results on Selector Adaptation in Behavior Treescited by 1
  7. 2017User Experience of the CoSTAR System for Instruction of Collaborative Robotscited by 1

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 6; 2025: 1; 2026: 5.

13 papers.

Sort:

By area: