Sense and avoid based on visual pose estimation for small UAS

Kang, Changkoo; Davis, Jason J.; Woolsey, Craig A.; Choi, Seongim

doi:10.1109/iros.2017.8206188

Cited by 8 publications

(5 citation statements)

References 12 publications

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“…Many researches have been conducted on autonomous collision avoidance of MQS. Authors in [18] propose the collision avoidance method based on estimating and predicting the agents' trajectory. A reference SAA system architecture is presented based on Boolean Decision Logics in [19].…”

Section: A Related Workmentioning

confidence: 99%

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A Physics-Based Safety Recovery Approach for Fault-Resilient Multi-Quadcopter Coordination

Emadi¹,

Harshvardhan²,

Rastgoftar³

2021

Preprint

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This paper develops a novel physics-based approach for fault-resilient multi-quadcopter coordination in the presence of abrupt quadcopter failure. Our approach consists of two main layers: (i) high-level physics-based guidance to safely plan the desired recovery trajectory for every healthy quadcopter and (ii) low-level trajectory control design by choosing an admissible control for every healthy quadcopter to safely recover from the anomalous situation, arisen from quadcopter failure, as quickly as possible. For the high-level trajectory planning, first, we consider healthy quadcopters as particles of an irrotational fluid flow sliding along streamline paths wrapping failed quadcopters in the shared motion space. We then obtain the desired recovery trajectories by maximizing the sliding speeds along the streamline paths such that the rotor angular speeds of healthy quadcopters do not exceed certain upper bounds at all times during the safety recovery. In the low level, a feedback linearization control is designed for every healthy quadcopter such that quadcopter rotor angular speeds remain bounded and satisfy the corresponding safety constraints. Simulation results are given to illustrate the efficacy of the proposed method.

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Section: A Related Workmentioning

confidence: 99%

“…In this subsection, we provide the input control for the non-linear state space system (18) to track the desired trajectory r d obtained from section III. Since we consider low speed quadcopters, agents enough time to update their path in case of failures.…”

Section: B Recovery Controlmentioning

confidence: 99%

A Physics-Based Safety Recovery Approach for Fault-Resilient Multi-Quadcopter Coordination

Emadi¹,

Harshvardhan²,

Rastgoftar³

2021

Preprint

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“…Theorem 4.1: If graph G i defining inter-agent communication in cluster i ∈ S contains a spanning tree, and communication weights are all positive and defined as given in Eq. (30), then matrices 1) and W i are Hurwitz.…”

Section: B Resilient Macroscopic Coordinationmentioning

confidence: 99%

“…Autonomous collision avoidance is one of the main LAUC challenges. Each UAS must have sense and avoid (SAA) [30]- [34] capabilities to avoid collision. SAA using laser/lidar [33] and machine vision [35] technologies is widely studied in the literature.…”

Section: Introductionmentioning

confidence: 99%

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Physics-Based Freely Scalable Continuum Deformation for UAS Traffic Coordination

Rastgoftar

Atkins

2020

IEEE Trans. Control Netw. Syst.

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This paper develops a novel physics-inspired traffic coordination approach and applies it to Unmanned Aircraft System (UAS) traffic management. We extend available physicsinspired approaches previously applied to 1-D traffic flow on highways and urban streets to support models of traffic coordination in higher dimension airspace for cases where no predefined paths exist. The paper considers airspace as a finite control volume while UAS coordination, treated as continuum deformation, is controlled at the airspace boundaries. By partitioning airspace into planned and unplanned spaces, the paper models nominal coordination in the planned airspace as the solution of a partial differential equation with spatiotemporal parameters. This paper also improves resilience to vehicle failures with a resilient boundary control algorithm to update the geometry of the planned space when UAS problems threaten safe coordination in existing navigable airspace channels. To support UAS coordination at the microscopic level, we propose clustering vehicles based on vehicle performance limits. UAS clusters, with each UAS treated as a particle of a virtual rigid body, use leader-follower containment to acquire the macroscopic desired trajectory.

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