Design and experimental evaluation of an omnidirectional leveling system for crawler orchard working platforms
Year: 2026
Type: article
Abstract: To address the challenges of large chassis inclination variations, low operational efficiency, and safety hazards encountered by crawler orchard working platform on complex terrain, this paper proposes an omnidirectional leveling scheme. A hydraulically actuated omnidirectional leveling system based on a five-point support mechanism was designed, and a “pitch-first, roll-second” adjustment strategy was formulated using a master-slave coupled hydraulic control methodology. Initially, the nonlinear mapping between leveling performance indicators and structural parameters was established through kinematic analysis. Subsequently, a comprehensive rollover model for the crawler orchard working platform was developed, yielding calculated longitudinal and lateral limiting rollover angles of 40.1° and 33.0°, respectively. The NSGA-II multi-objective genetic algorithm was then employed to optimize the structural parameters, achieving an optimal balance between hydraulic cylinder thrust and system responsiveness. A co-simulation model integrating hydraulic and mechanical systems was constructed using AMESim. Simulation results indicated a maximum adjustment range of ±12° longitudinally and ±9.3° laterally, with corresponding leveling times of 3.0 s and 2.5 s. Finally, prototype performance tests were conducted. The experimental results demonstrated a maximum static leveling error of 0.55°, with overall leveling times consistently under 3.0 s. During dynamic operation, the platform maintained longitudinal and lateral angles within a ±2° stability threshold for over 71% of the duration. The prototype experimental results were consistent with the simulation data, validating the effectiveness of the omnidirectional leveling system. This research offers theoretical references and technical support for the development of leveling systems in agricultural machinery.
Source: Smart Agricultural Technology
Authors: Yuyang Liu, Jingbin Li, Zhiyuan Zhang, Longpeng Ding, Yajie Liu, Gang Hou, Kaihao Sun, Zeyi Li
Language: English
Subfield: Mechanical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,770
Award: G7240460576
OpenAlex ID: W7136332208
