Related Experiment Video
Updated: May 25, 2025

Tracking Rats in Operant Conditioning Chambers Using a Versatile Homemade Video Camera and DeepLabCut
Published on: June 15, 2020
ZPTM: Zigzag Path Tracking Method for Agricultural Vehicles Using Point Cloud Representation
Shuang Yang1, Engen Zhang1, Yufei Liu2
1School of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo 255000, China.
Abstract:
Automatic navigation, as one of the modern technologies in farming automation, enables unmanned driving and operation of agricultural vehicles. In this research, the ZPTM (Zigzag Path Tracking Method) was proposed to reduce the complexity of path planning by using a point cloud consisting of a series of anchor points with spatial information, which are obtained from orthophotos taken by UAVs (Unmanned Aerial Vehicles) to represent the curved path in the zigzag. A local straight path was created by linking two adjacent anchor points, forming the local target path to be tracked, which simplified the navigation algorithm for zigzag path tracking. A nonlinear feedback function was established, using both lateral and heading errors as inputs for determining the desired heading angle of agricultural vehicles, which were guided along the local target path with minimal errors. A GUI (Graphic User Interface) was designed on the navigation terminal to visualize and monitor the working process of agricultural vehicles in automatic navigation, displaying interactive controls and components, including representations of the zigzag path and the agricultural vehicle using affine transformation. A high-clearance sprayer equipped with an automatic navigation system was utilized as the test platform to evaluate the proposed ZPTM. Zigzag navigation tests were conducted to explore the impact of path tracking parameters, including path curvature, moving speed, and spacing between anchor points, on zigzag navigation performance. Based on these tests, a regression model was established to optimize these parameters for achieving accurate and smooth movement. Field test results showed that the maximum error, average error, and RMS (Root Mean Square) error in the zigzag navigation were 3.30 cm, 2.04 cm, and 2.27 cm, respectively. These results indicate that the point cloud path-based ZPTM in this research demonstrates adequate stability, accuracy, and applicability in zigzag navigation.
More Related Videos
08:13SwarmSight: Real-time Tracking of Insect Antenna Movements and Proboscis Extension Reflex Using a Common Preparation and Conventional Hardware
Published on: December 25, 2017
08:04Fully Automated Leg Tracking in Freely Moving Insects using Feature Learning Leg Segmentation and Tracking FLLIT
Published on: April 23, 2020
Related Concept Videos
Relative Motion Analysis using Rotating Axes-Problem Solving
Here, in order to determine the magnitude of velocity and acceleration for point...
Relative Motion Analysis using Rotating Axes
However, to express the relative position of point B relative to point A, an additional frame of reference, denoted as x'y', is necessary. This additional frame not only translates but also rotates relative to the fixed frame, making it...
Light Acquisition
Absolute Motion Analysis- General Plane Motion
As the drone's propellers rotate, an upward force is generated that counteracts the force of gravity, enabling the drone to lift off from the ground. This initial movement of the drone is along a straight path, representing a form of translational motion. In this phase, every point on the...
Field Application of Global Positioning System
Relative Motion Analysis using Rotating Axes - Acceleration
Time differentiation is...