VFO feedback control using positively-invariant funnels for mobile robots travelling in polygonal worlds with bounded curvature of motion

Gawron, Tomasz; Michałek, Maciej Marcin

doi:10.1109/aim.2017.8014006

Cited by 7 publications

(3 citation statements)

References 10 publications

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“…To guarantee safety without sampling, most existing works rely on Lyapunov theory and reachable set overapproximations. Building on the seminal work of [11], sequential composition of funnels [32] (reachable set approximations) offers effective means of guaranteeing safe navigation [39,31,19,20]. Using sum-of-squares (SOS) optimization [38], these techniques can deal with nonlinear systems directly and may handle nonholonomic constraints and bounded disturbances.…”

Section: A Related Workmentioning

confidence: 99%

“…V, we choose a stabilizing control gain K for the linear system in (5) and re-order the states as z = col (x, y, ẋ, ẏ, ẍ, ÿ), arriving at the system in (8). The reminder of the control design, including the local safe zone and projected goal computations in (19) and (20), is agnostic to the original system dynamics.…”

Section: Application: Ackermann-drive Robotmentioning

confidence: 99%

“…It is important to note that the controller does not rely on the map of the environment. It only tracks the geometric path provided by A * , relying on the lidar scanner to evaluate the local safe zone LS(s) in (19) and determine the the local projected goal ḡ(s) in (20). The governor regulates the tracking speed using the output peak bounds proposed in Sec.…”

Section: B Simulated Ackermann-drive Navigationmentioning

confidence: 99%

See 2 more Smart Citations

Safe Robot Navigation in Cluttered Environments using Invariant Ellipsoids and a Reference Governor

Li,

Duong,

Atanasov

2020

Preprint

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This paper considers the problem of safe autonomous navigation in unknown environments, relying on local obstacle sensing. We consider a control-affine nonlinear robot system subject to bounded input noise and rely on feedback linearization to determine ellipsoid output bounds on the closedloop robot trajectory under stabilizing control. A virtual governor system is developed to adaptively track a desired navigation path, while relying on the robot trajectory bounds to slow down if safety is endangered and speed up otherwise. The main contribution is the derivation of theoretical guarantees for safe nonlinear system path-following control and its application to autonomous robot navigation in unknown environments.

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