ROOCAug 24, 2016

Multi-objective Compositions for Collision-Free Connectivity Maintenance in Teams of Mobile Robots

arXiv:1608.06887v1120 citations
Originality Incremental advance
AI Analysis

This addresses safety and coordination challenges in mobile robotics, but it is incremental as it builds on existing barrier function methods.

The paper tackled the problem of ensuring collision avoidance and connectivity in multi-robot teams by proposing compositional barrier functions to systematically combine multiple objectives, and it experimentally verified the approach on a team of four robots with provable guarantees.

Compositional barrier functions are proposed in this paper to systematically compose multiple objectives for teams of mobile robots. The objectives are first encoded as barrier functions, and then composed using AND and OR logical operators. The advantage of this approach is that compositional barrier functions can provably guarantee the simultaneous satisfaction of all composed objectives. The compositional barrier functions are applied to the example of ensuring collision avoidance and static/dynamical graph connectivity of teams of mobile robots. The resulting composite safety and connectivity barrier certificates are verified experimentally on a team of four mobile robots.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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