The chassis configuration serves as the mobility foundation of agricultural robots, directly determining their trafficability, stability, and intelligent operation in complex fields. Existing research lacks a systematic analysis of the evolution and adaptation principles of mainstream chassis technologies. This review addresses this gap by proposing a dual-dimensional framework—“structural design principles and dynamic adaptive control”—to evaluate wheeled, tracked, and wheel-legged hybrid chassis. Our analysis reveals that (1) wheeled chassis achieve refinement through efficiency-driven operation in structured environments but are limited by rigid wheel–ground contact; (2) tracked chassis enhance performance on soft or sloped terrain via technologies like contour-adaptive tracks, albeit with increased energy consumption; and (3) wheel-legged hybrid chassis represent a shift towards active terrain overcoming, offering superior adaptability at the cost of high control complexity. Finally, we synthesize persistent challenges and identify future breakthroughs in terrain–vehicle coupled modeling and multi-modal control, which will drive the evolution towards intelligent, mechatronic–hydraulic integrated platforms.

To address the suboptimal leveling performance and insufficient slope stability of existing agricultural machinery chassis in hilly and mountainous regions, this study proposes an innovative omnidirectional leveling system based on a “double-layer frame” crawler-type agricultural chassis. The system employs servo-electric cylinders as its actuation components. A control model for the servo-electric cylinders has been established, accompanied by the design of an adaptive sliding mode controller (ASMC). A co-simulation platform was developed utilizing Matlab/Simulink and Adams to evaluate system performance. Comparative simulations were conducted between the ASMC and a conventional PID controller, followed by comprehensive machine testing. Experimental results demonstrate that the proposed double-layer frame crawler chassis achieves longitudinal leveling adjustments of up to 25° and lateral adjustments of 20°. Through structural optimization and the application of ASMC (in contrast to PID), both longitudinal and lateral leveling response times were reduced by 1.12 s and 0.95 s, respectively. Furthermore, leveling velocities increased by a factor of 1.5 in the longitudinal direction and by a factor of 1.3 in the lateral direction, while longitudinal and lateral angular accelerations decreased by 15.8% and 17.1%, respectively. Field tests confirm the system’s capability for adaptive leveling on inclined terrain, thereby validating the enhanced performance of the proposed omnidirectional leveling system.

The suspension system can adapt to different road excitations by adjusting its own stiffness or damping, or outputting active driving force, thereby improving the comprehensive dynamic performance of the vehicle, including ride comfort and vehicle handling. As the automotive industry’s requirements for “intelligence, comfort, and safety” continue to increase, the intelligence of suspension systems has become a research hotspot for scientific research institutions and enterprises, with broad development prospects. This article reviews the current development status of automotive suspensions and introduces the working principles and research status of different types of suspension systems, such as passive suspensions, semi-active suspensions, active suspensions, and electromagnetic suspensions. In addition, it summarizes the control methods of vehicle intelligent suspensions, including classical control, modern control, and intelligent control, and expounds the advantages and disadvantages of each control strategy. Finally, it summarizes the challenges and development trends faced by suspension systems. This review can provide technical reference for researchers engaged in the study of intelligent suspension under the modern chassis architecture and offer direction guidance for the development of key suspension technologies.

The scenario adaptability of agricultural machinery chassis in hilly and mountainous regions has become a key area of innovation in modern agricultural equipment development in China. Due to the fragmented nature of farmland, steep terrain (often exceeding 15°), complex topography, and limited suitability for mechanization, traditional agricultural machinery experiences significantly reduced operational efficiency—typically by 30% to 50%—along with poor mobility. These limitations impose serious constraints on grain yield stability and the advancement of agricultural modernization. Therefore, enhancing the scenario-adaptive performance of chassis systems (e.g., slope adaptability ≥ 25°, lateral tilt stability > 30°) is a major research priority for China’s agricultural equipment industry. This paper presents a systematic review of the global development status of agricultural machinery chassis tailored for hilly and mountainous environments. It focuses on three core subsystems—power systems, traveling systems, and leveling systems—and analyzes their technical characteristics, working principles, and scenario-specific adaptability. In alignment with China’s “Dual Carbon” strategy and the unique operational requirements of hilly–mountainous areas (such as high gradients, uneven terrain, and small field sizes), this study proposes three key technological directions for the development of intelligent agricultural machinery chassis: (1) Multi-mode traveling mechanism design: Aimed at improving terrain traversability (ground clearance ≥400 mm, obstacle-crossing height ≥ 250 mm) and traction stability (slip ratio < 15%) across diverse landscapes. (2) Coordinated control algorithm optimization: Designed to ensure stable torque output (fluctuation rate < ±10%) and maintain gradient operation efficiency (e.g., less than 15% efficiency loss on 25° slopes) through power–drive synergy while also optimizing energy management strategies. (3) Intelligent perception system integration: Facilitating high-precision adaptive leveling (accuracy ± 0.5°, response time < 3 s) and enabling terrain-adaptive mechanism optimization to enhance platform stability and operational safety. By establishing these performance benchmarks and focusing on critical technical priorities—including terrain-adaptive mechanism upgrades, energy-drive coordination, and precision leveling—this study provides a clear roadmap for the development of modular and intelligent chassis systems specifically designed for China’s hilly and mountainous regions, thereby addressing current bottlenecks in agricultural mechanization.