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从感知到运动，开发自主应用，优化系统级行为

机器人与自主系统介绍在物理环境中移动和操作以执行目标导向的动作的平台系统，如汽车、飞机、机器人和无人机。您可以通过多个工具箱中的工具和算法来仿真、估计、导航和控制平台状态（如它们的位置和速度）以及监控物理环境。具体来说，您可以：

使用各种坐标系和地图来设计、建模和仿真自主系统场景，包括平台、轨迹、路径、传感器和环境。
生成检测并进行分类，估计平台，并获得各种环境地图。
基于不同的运动特性，使用不同的路径规划算法来规划机器人、无人机和汽车的路径。
使用多种运动控制算法和策略控制机器人、无人机和汽车。
将软件设计与机器人操作系统 (ros) 连接起来，并在硬件上部署您设计的估计、导航和控制算法。

适用产品：机器人与自主系统

automated driving toolbox

design, simulate, and test adas and autonomous driving systems

robotics system toolbox

design, simulate, test, and deploy robotics applications

uav toolbox

design, simulate, and deploy uav applications

navigation toolbox

design, simulate, and deploy algorithms for autonomous navigation

ros toolbox

design, simulate, and deploy ros-based applications

sensor fusion and tracking toolbox

design, simulate, and test multisensor tracking and positioning systems

主题

场景设计和仿真

(roadrunner)
use roadrunner scene editing software to create a simple road network.
(automated driving toolbox)
use the driving scenario designer app to create a driving scenario and generate sensor detections and point cloud data from the scenario.
(uav toolbox)
visualize sensors in a simulation environment that uses unreal engine® from epic games®.
control and simulate multiple warehouse robots (robotics system toolbox)
control and simulate multiple robots working in a warehouse facility or distribution center.

检测和分类

detect, classify, and track vehicles using lidar (lidar toolbox)
detect, classify, and track vehicles by using lidar point cloud data captured by a lidar sensor mounted on an ego vehicle.
lidar 3-d object detection using pointpillars deep learning (lidar toolbox)
train a pointpillars network for object detection in point clouds.

定位和地图构建

build a map from lidar data (automated driving toolbox)
process 3-d lidar sensor data to progressively build a map, with assistance from inertial measurement unit (imu) readings.
build map and localize using segment matching (automated driving toolbox)
build a map with lidar data and localize the position of a vehicle on the map using segmatch, a place recognition algorithm based on segment matching.
stereo visual slam for uav navigation in 3d simulation (uav toolbox)
generate a map for a city block scene in an unreal engine environment using stereo visual simultaneous localization and mapping.

态势感知和状态估计

extended object tracking of highway vehicles with radar and camera (sensor fusion and tracking toolbox)
track highway vehicles around an ego vehicle as extended objects that span multiple sensor resolution cells.
visual-inertial odometry using synthetic data (sensor fusion and tracking toolbox)
estimate the pose (position and orientation) of a ground vehicle using an inertial measurement unit (imu) and a monocular camera.

运动规划

(sensor fusion and tracking toolbox)
dynamically plan the motion of an autonomous vehicle based on estimates of the surrounding environment.
motion planning with rrt for fixed-wing uav (uav toolbox)
plan the motion of a fixed-wing unmanned aerial vehicle (uav) using the rapidly exploring random tree (rrt) algorithm given a start and goal pose on a 3-d map.
pick-and-place workflow in gazebo using point-cloud processing and rrt path planning (robotics system toolbox)
set up an end-to-end, pick-and-place workflow for a robotic manipulator like the kinova® gen3.

运动控制

highway lane following with roadrunner scene (automated driving toolbox)
simulate a highway lane following application using a scene created in the roadrunner 3d scene editing tool.
path following with obstacle avoidance in simulink® (navigation toolbox)
use simulink to avoid obstacles while following a path for a differential drive robot.
control and simulate multiple warehouse robots (robotics system toolbox)
control and simulate multiple robots working in a warehouse facility or distribution center.

硬件部署

(sensor fusion and tracking toolbox)
obtain data from an invensense mpu-9250 imu sensor, and to use the 6-axis and 9-axis fusion algorithms in the sensor data to compute orientation of the device.
sign-following robot with ros in matlab (ros toolbox)
control a simulated robot running on a separate ros-based simulator over a ros network using matlab^®.
localize turtlebot using monte carlo localization algorithm (navigation toolbox)
apply the monte carlo localization algorithm on a turtlebot® robot in a simulated gazebo® environment.

精选示例

uav package delivery

implement a small multicopter simulation to takeoff, fly, and land in a city environment.

visualize automated parking valet using unreal engine simulation

visualize vehicle motion in unreal engine^® using a parking valet system constructed in simulink^®.