# SMART-OC: A Real-time Time-risk Optimal Replanning Algorithm for Dynamic Obstacles and Spatio-temporally Varying Currents

arXiv: https://arxiv.org/abs/2508.09508 · HTML: https://mlsanity.com/paper/2508.09508/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 35 references that are in the map.
- First posted on arXiv 13 Aug 2025.

## Builds on (most cited first, 7 of 7)

- [CARE: Cooperative Autonomy for Resilience and Efficiency of Robot Teams for Complete Coverage of Unknown Environments under Robot Failures](https://mlsanity.com/paper/1905.12191/) (2019)
- [ε^*+: An Online Coverage Path Planning Algorithm for Energy-constrained Autonomous Vehicles](https://mlsanity.com/paper/2008.13041/) (2020)
- [CT-CPP: Coverage Path Planning for 3D Terrain Reconstruction Using Dynamic Coverage Trees](https://mlsanity.com/paper/2010.09231/) (2020)
- [SMART: Self-Morphing Adaptive Replanning Tree](https://mlsanity.com/paper/2305.06487/) (2023)
- [Rapid Path Planning for Dubins Vehicles under Environmental Currents](https://mlsanity.com/paper/1909.04105/) (2019)
- [Generalized Multi-Speed Dubins Motion Model](https://mlsanity.com/paper/2402.01122/) (2024)
- [Distance and Steering Heuristics for Streamline-Based Flow Field Planning](https://mlsanity.com/paper/2005.06718/) (2020)

## Built on by (most cited first, 1 of 1)

- [SMART-3D: Three-Dimensional Self-Morphing Adaptive Replanning Tree](https://mlsanity.com/paper/2509.16812/) (2025)

## Abstract (arXiv)

Typical marine environments are highly complex with spatio-temporally varying currents and dynamic obstacles, presenting significant challenges to Unmanned Surface Vehicles (USVs) for safe and efficient navigation. Thus, the USVs need to continuously adapt their paths with real-time information to avoid collisions and follow the path of least resistance to the goal via exploiting ocean currents. In this regard, we introduce a novel algorithm, called Self-Morphing Adaptive Replanning Tree for dynamic Obstacles and Currents (SMART-OC), that facilitates real-time time-risk optimal replanning in dynamic environments. SMART-OC integrates the obstacle risks along a path with the time cost to reach the goal to find the time-risk optimal path. The effectiveness of SMART-OC is validated by simulation experiments, which demonstrate that the USV performs fast replannings to avoid dynamic obstacles and exploit ocean currents to successfully reach the goal.