Exogenous Disturbance Estimation for Autonomous Navigation around Small Celestial Bodies

Viswanathan, Vignesh Kottayam; Papadimitriou, Andreas; Banerjee, Abhisek; Mansouri, Sina Sharif; Nikolakopolous, George

doi:10.1109/cdc51059.2022.9993130

Cited by 2 publications

(1 citation statement)

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“…Robot autonomy, at its current stage, has consolidated extensive and multi-disciplinary use cases by providing a profitable and efficient mode of fulfilment of missions [1,2]. Primarily due to the increased capability and ease of onboard autonomy to be adapted and implemented based on the mission scenario, autonomous robots have prevailed to serve the needs put forth by industries worldwide.…”

Section: Introductionmentioning

confidence: 99%

Towards Visual Inspection of Distributed and Irregular Structures: A Unified Autonomy Approach

Viswanathan,

Lindqvist,

Satpute

et al. 2023

J Intell Robot Syst

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This paper highlights the significance of maintaining and enhancing situational awareness in Urban Search and Rescue (USAR) missions. It focuses specifically on investigating the capabilities of Unmanned Aerial Vehicles (UAV) equipped with limited sensing capabilities and onboard computational resources to perform visual inspections of apriori unknown fractured and collapsed structures in unfamiliar environments. The proposed approach, referred to as First Look Inspect-Explore (FLIE), employs a flexible bifurcated behavior tree that leverages real-time RGB image and depth cloud data. By employing a recursive and reactive synthesis of safe view pose within the inspection module, FLIE incorporates a novel active visual guidance scheme for identifying previously inspected surfaces. Furthermore, the integration of a tiered hierarchical exploration module with the visual guidance system enables the UAV to navigate towards new and unexplored structures without relying on a map. This decoupling reduces memory overhead and computational effort by eliminating the need to plan based on an incrementally built, error-prone global map. The proposed autonomy is extensively evaluated through simulation and experimental verification under various scenarios and compared against state-of-art approaches, demonstrating its performance and effectiveness.

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Section: Introductionmentioning

confidence: 99%