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Article summary:
1. This article proposes a search-based planning method to compute dynamically feasible trajectories for a quadrotor flying in an obstacle-cluttered environment.
2. The proposed approach is able to generate resolution-complete, safe, and dynamically feasible trajectories efficiently by exploiting the explicit solution of a Linear Quadratic Minimum Time problem.
3. The approach plans globally-optimal trajectories based on time and control efforts, and can be used for online replanning during fast quadrotor navigation in various cluttered environments.
Article analysis:
The article is generally reliable and trustworthy as it provides evidence for its claims through references to previous works and experiments conducted with the proposed approach. The authors provide detailed descriptions of their methods and results, which are supported by figures and tables that illustrate the effectiveness of their approach. Furthermore, the authors acknowledge potential limitations of their work such as the need for further research into more efficient search algorithms or improved heuristics.
However, there are some points that could be improved upon in terms of trustworthiness and reliability. For example, while the authors do mention potential risks associated with their approach (e.g., collisions), they do not provide any details on how these risks can be mitigated or avoided. Additionally, while the authors compare their results to those obtained from state-of-the-art quadratic programming approaches, they do not explore any counterarguments or alternative approaches that may yield better results than theirs. Finally, there is no discussion on how this work could be applied in real world scenarios or what implications it may have on future research in this field.