Skip to main content
eScholarship
Open Access Publications from the University of California

UC San Diego

UC San Diego Electronic Theses and Dissertations bannerUC San Diego

Multi-RRT for Efficient Information-Theoretic Exploration

  • Author(s): Khoury, Alexander
  • Advisor(s): Atanasov, Nikolay
  • et al.
Abstract

The ability for a mobile robot to autonomously and efficiently build a map of an environment, termed robotic exploration, is long sought after by researchers and industry professionals. Existing work in this field focuses on local continuous-space optimization or global discrete-space search over hand-designed graph structures with information-theoretic objectives. Global optimization is critical in practice to achieve a precise trade-off between exploration of new areas and map refinement in observed areas. Many existing approaches solve the optimization with a gradient-based method with poor convergence properties, or by heavily constraining the optimization to a lower dimensional search space. A major contribution of this thesis is the automated construction of a graph of potential robot trajectories, optimized to capture long-horizon maximization of the map's information content. The graph represents a significantly larger space of promising robot trajectories compared to existing motion primitive approaches, leading to a combined improvement in exploration speed and uncertainty reduction. This work also provides a thorough evaluation and comparison of several state-of-the-art autonomous exploration techniques over a large dataset of simulated environments as well as several physical robot trials in cluttered environments.

Main Content
For improved accessibility of PDF content, download the file to your device.
Current View