Projects

Welcome to the Projects page, offering a comprehensive insight into my research endeavors in autonomous robotics. Each project represents a journey into the complexities of algorithmic motion planning and task execution for both single and multi-robot systems. From contributing to the "Open Motion Planning Library," a widely used C++ framework, to publishing research papers that advance the field, these projects embody a dedication to pushing the boundaries of knowledge. Dive into the details of each research project, exploring methodologies, challenges, and the impact on the evolving landscape of robotics. Whether you are a fellow researcher, student, or enthusiast, this page invites you to explore the depth and contributions of each project in the pursuit of advancing autonomous systems.

Work

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MR-OMPL

An extension of the revered Open Motion Planning Library (OMPL) to account for multi-robot motion planning.
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K-CBS

Kinodynamic Conflict-Based Search (K-CBS) is a complete and scalable MRMP algorithm.
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CCK-CBS

We adapt K-CBS for chance-constrained multi-robot motion planning (CC-MRMP) where the robots are subject to both process and measurement noise.
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Online Fault ID

We use M-ary Bayesian Hypothesis Testing to verify nominal system performance (or lack thereof) in real-time.
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XG-CBS

Explanation-Guided Conflict-Based Search (XG-CBS) extends CBS for MAPF to account for interpretability and thus producing more easily validated plans.
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MAPS-X

Sampling-based random-tree algorithms for MRMP are extended to consider plan interpretability and thus producing more easily validated plans.