Exploiting spatial group error and synchrony for a unicycle tracking controller
Trajectory tracking for the kinematic unicycle has been heavily studied for several decades. The unicycle admits a natural $\SE(2)$ symmetry, a key structure exploited in many of the most successful nonlinear controllers in the literature. To the author's knowledge however, all prior work has used a body-fixed, or left-invariant, group error formulation for the study of the tracking problem. In this paper, we consider the spatial, or right-invariant, group error in the design of a tracking controller for the kinematic unicycle. We provide a physical interpretation of the right-invariant error and go on to show that the associated error dynamics are drift-free, a property that is not true for the body-fixed error. We exploit this property to propose a simple nonlinear control scheme for the kinematic unicycle and prove almost-global asymptotic stability of this control scheme for a class of persistently exciting trajectories. We also verify performance of this control scheme in simulation for an example trajectory.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Global and local synchrony of coupled neurons in small-world networks
Synchronous firing of neurons is thought to play important functional roles such as feature binding and switching of cognitive states. Although synchronization has mainly been investigated using model neurons with simple…
Seasonality, density dependence and spatial population synchrony
Spatial population synchrony has been the focus of theoretical and empirical studies for decades, in the hopes of understanding mechanisms and interactions driving ecological dynamics. In many systems, it is well-known t…
Time SeriesTime Series AnalysisLong-range dispersal promotes spatial synchrony but reduces the length and time scales of synchronous fluctuations
Synchronous oscillations of spatially disjunct populations are widely observed in ecology. Even in the absence of spatially synchronized exogenous forces, metapopulations may synchronize via dispersal. For many species, …
Pose Uncertainty Aware Movement Synchrony Estimation via Spatial-Temporal Graph Transformer
Movement synchrony reflects the coordination of body movements between interacting dyads. The estimation of movement synchrony has been automated by powerful deep learning models such as transformer networks. However, in…
Activity RecognitionContrastive LearningHuman Activity RecognitionKnowledge Distillation+1Event-Triggered Polynomial Control for Trajectory Tracking by Unicycle Robots
This paper proposes an event-triggered polynomial control method for trajectory tracking by unicycle robots. In this method, each control input between two consecutive events is a polynomial and its coefficients are chos…