In context
In early 2024, multi-robot systems were increasingly deployed for inspection and maintenance in underground pipeline networks, where narrow channels permit only one robot at a time. Existing multi-robot path planning algorithms struggled with frequent endpoint blockages and position interlocking—situations where robots mutually block each other in confined spaces—limiting operational efficiency and reliability.
What was reported
Researchers proposed DPiSIPP, a dynamic-priority Safe-Interval Path Planning (SIPP) algorithm with intermediate points, specifically designed for underground pipeline environments. The algorithm introduces a deterministic re-scheduling method: robots encountering endpoint blockages are given higher planning priority, allowing them to be rescheduled first and thereby clearing the blockage.
For position interlocking problems, DPiSIPP adds an intermediate point to segment the path of affected robots. This approach either directly resolves the interlocking relationship or converts the problem into an endpoint blockage, which can then be handled by the priority mechanism.
Experimental results in underground pipeline scenarios showed that DPiSIPP improved solution success rates by up to 30% compared to Anytime SIPP and WSIPPd (weighted SIPP with duplicate states), and by up to 10% compared to an enhanced Conflict-Based Search (CBS) algorithm.
Why it mattered
By addressing two common failure modes in confined multi-robot coordination, DPiSIPP offered a practical improvement for autonomous operations in infrastructure networks, potentially reducing downtime and human intervention in sewer, gas, and water pipeline inspection—an area where reliable automation is critical for safety and cost efficiency.
"The experimental results demonstrate that the success rate of the proposed DPiSIPP algorithm can outperform Anytime SIPP, WSIPPd, and enhanced CBS algorithms by up to 30%, 30%, and 10%, respectively."
Source: 《机器人》期刊 (robot.sia.cn) · Published 2024-02-04 · “一种面向地下管网环境的多机器人路径规划算法”