5,264 research outputs found
Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age
Simultaneous Localization and Mapping (SLAM)consists in the concurrent
construction of a model of the environment (the map), and the estimation of the
state of the robot moving within it. The SLAM community has made astonishing
progress over the last 30 years, enabling large-scale real-world applications,
and witnessing a steady transition of this technology to industry. We survey
the current state of SLAM. We start by presenting what is now the de-facto
standard formulation for SLAM. We then review related work, covering a broad
set of topics including robustness and scalability in long-term mapping, metric
and semantic representations for mapping, theoretical performance guarantees,
active SLAM and exploration, and other new frontiers. This paper simultaneously
serves as a position paper and tutorial to those who are users of SLAM. By
looking at the published research with a critical eye, we delineate open
challenges and new research issues, that still deserve careful scientific
investigation. The paper also contains the authors' take on two questions that
often animate discussions during robotics conferences: Do robots need SLAM? and
Is SLAM solved
Event-Triggered Multi-Lane Fusion Control for 2-D Vehicle Platoon Systems with Distance Constraints
This paper investigates the event-triggered fixedtime multi-lane fusion control for vehicle platoon systems with
distance keeping constraints where the vehicles are spread in
multiple lanes. To realize the fusion of vehicles in different lanes,
the vehicle platoon systems are firstly constructed with respect to
a two-dimensional (2-D) plane. In case of the collision and loss of
effective communication, the distance constraints for each vehicle
are guaranteed by a barrier function-based control strategy.
In contrast to the existing results regarding the command
filter techniques, the proposed distance keeping controller can
constrain the distance tracking error directly and the error
generated by the command filter is coped with by adaptive fuzzy
control technique. Moreover, to offset the impacts of the unknown
system dynamics and the external disturbances, an unknown
input reconstruction method with asymptotic convergence is
developed by utilizing the interval observer technique. Finally,
two relative threshold triggering mechanisms are utilized in the
proposed fixed-time multi-lane fusion controller design so as to
reduce the communication burden. The corresponding simulation
results also verify the effectiveness of the proposed strategy
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