RUL-Aware RRT*: Degradation-Balanced Motion Planning for Robotic Manipulators

2026-10-01

AI Summary

This study addresses the problem of bottleneck failures caused by uneven joint degradation in robotic manipulators during long-term operation. To this end, it proposes an improved RRT* motion planning method informed by remaining useful life (RUL) estimation. This algorithm pioneers the deep integration of health feedback with path search, dynamically balancing wear disparities across joints through adaptive load allocation. By overcoming the limitations of conventional planners that neglect degradation equalization, the proposed approach effectively delays the onset of bottleneck failures and significantly enhances the long-term reliability and durability of robotic manipulators.

Abstract

Robotic manipulators operating over long durations often experience uneven joint degradation, which causes the weakest actuator to fail prematurely, leads to unplanned downtime, and results in significant operational losses. Traditional motion-planning algorithms do not account for joint health conditions and therefore tend to exacerbate this imbalance during extended operation. To address this challenge, this study introduces the RUL-aware RRT*, a motion-planning method that incorporates joint remaining useful life information into the planning process and adaptively adjusts joint usage in response to evolving health conditions. The method is evaluated across three representative scenarios, namely the Full Health Scenario (FHS), the Heterogeneous Degradation Scenario (HDS), and the Local Degradation Scenario (LDS). The results show that the RUL-aware RRT* effectively suppresses degradation imbalance, delays the emergence of bottleneck failures, and improves the long-term reliability of the robotic system during extended operation. These findings demonstrate that integrating health feedback into motion planning provides a practical and robust pathway for enhancing the durability and operational resilience of manipulators subject to continuous wear.

Problem

• Robotic Manipulators
• Motion Planning
• Joint Degradation
• Remaining Useful Life
• Reliability

Innovation

• Remaining Useful Life (RUL)
• Motion Planning
• RRT*
• Degradation Balance
• Robotic Manipulators