mlsanityData to 14 Oct 2026

Towards Blended Reactive Planning and Acting using Behavior Trees

arXiv 1611.00230 ↗First posted 1 Nov 2016cs.RO cs.AIcited by 21

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Abstract (arXiv)

In this paper, we show how a planning algorithm can be used to automatically create and update a Behavior Tree (BT), controlling a robot in a dynamic environment. The planning part of the algorithm is based on the idea of back chaining. Starting from a goal condition we iteratively select actions to achieve that goal, and if those actions have unmet preconditions, they are extended with actions to achieve them in the same way. The fact that BTs are inherently modular and reactive makes the proposed solution blend acting and planning in a way that enables the robot to efficiently react to external disturbances. If an external agent undoes an action the robot reexecutes it without re-planning, and if an external agent helps the robot, it skips the corresponding actions, again without replanning. We illustrate our approach in two different robotics scenarios.

Key facts. Cited by 21 papers in the map (data through 14 Oct 2026). First posted on arXiv 1 Nov 2016.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 2; 2022: 2; 2023: 2; 2024: 6; 2025: 5; 2026: 4.

21 papers.

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  1. 2023AutoTAMP: Autoregressive Task and Motion Planning with LLMs as Translators and Checkerscited by 113
  2. 2022Behavior Trees in Robot Control Systemscited by 13
  3. 2024Integrating Intent Understanding and Optimal Behavior Planning for Behavior Tree Generation from Human Instructionscited by 12
  4. 2025Code-as-Symbolic-Planner: Foundation Model-Based Robot Planning via Symbolic Code Generationcited by 10
  5. 2021Combining Planning and Learning of Behavior Trees for Robotic Assemblycited by 9
  6. 2024Task and Motion Planning for Execution in the Realcited by 6
  7. 2024A Study on Training and Developing Large Language Models for Behavior Tree Generationcited by 4
  8. 2024HBTP: Heuristic Behavior Tree Planning with Large Language Model Reasoningcited by 4
  9. 2025A Unified Framework for Real-Time Failure Handling in Robotics Using Vision-Language Models, Reactive Planner and Behavior Treescited by 4
  10. 2024Adaptive Manipulation using Behavior Treescited by 2
  11. 2025MRBTP: Efficient Multi-Robot Behavior Tree Planning and Collaborationcited by 2
  12. 2026From Prompts to Pavement: LMMs-based Agentic Behavior-Tree Generation Framework for Autonomous Vehiclescited by 2
9 more
  1. 2023An Extended Convergence Result for Behaviour Tree Controllerscited by 1
  2. 2021Meta-Modeling of Assembly Contingencies and Planning for Repaircited by 0
  3. 2022Behavior Tree-Based Task Planning for Multiple Mobile Robots using a Data Distribution Servicecited by 0
  4. 2024Interpretable Responsibility Sharing as a Heuristic for Task and Motion Planningcited by 0
  5. 2025Acting and Planning with Hierarchical Operational Models on a Mobile Robot: A Study with RAE+UPOMcited by 0
  6. 2025Advancing Shared and Multi-Agent Autonomy in Underwater Missions: Integrating Knowledge Graphs and Retrieval-Augmented Generationcited by 0
  7. 2026Progress Constraints for Reinforcement Learning in Behavior Treescited by 0
  8. 2026Contract-Grounded Behavior Tree Synthesis via Coding Agentscited by 0
  9. 2026APTree: Extended Behavior Trees for Adaptive and Scalable Automated Robotic Task Planning in Constructioncited by 0