Grid-centric perception is a crucial field for mobile robot perception and navigation.
Nonetheless, grid-centric perception is less prevalent than object-centric perception for …

When multiple robots are involved in the process of simultaneous localization and mapping
(SLAM), a global map should be constructed by merging the local maps built by individual …

In this paper, we propose a survey of the Simultaneous Localization And Mapping (SLAM)
field when considering the recent evolution of autonomous driving. The growing interest …

Local mapping is valuable for many real-time applications of intelligent vehicle systems.
Multivehicle cooperative local mapping can bring considerable benefits to vehicles …

边缘计算在自动驾驶的环境感知和数据处理方面有着极其重要的应用. 自动驾驶汽车可以通过从
边缘节点获得环境信息来扩大自身的感知范围, 也可以向边缘节点卸载计算任务以解决计算资源 …

Multi-robot mapping and environment modeling have several advantages that make it an
attractive alternative to the mapping with a single robot: faster exploration, higher fault …

Ground truth data plays an important role in validating perception algorithms and in
developing data-driven models. Yet, generating ground truth data is a challenging process …

In the field of autonomous navigation, perception of the driving scene is one of the essential
elements. Existing solutions combine on-board exteroceptive sensors, and are capable of …

In this paper, we propose a new approach to the decentralized Simultaneous Localization
And Mapping (SLAM) problem. The goal is to demonstrate the feasibility of decentralized …

The research theme of this dissertation is the multiple-vehicles cooperative perception (or
cooperative perception) applied in the context of intelligent vehicle systems. The general …