Browse Topic: Chassis
To solve the poor mobility of traditional camping vehicle chassis in complex terrains and confined spaces, this paper proposes an underactuated omnidirectional mobile chassis for outdoor camping vehicles. The chassis adopts a coupled commutation mechanism (double-crank elastic special-shaped connecting rods cross sliders), allowing each wheel to realize two motion modes (omnidirectional translation, in-situ rotation) with just one drive motor, reducing system complexity and cost. A control system based on the RoboMaster Development Board C Type integrates PID angle-loop control and motor speed-current dual closed-loop control for motion stability. Kinematic models for these two modes are established to derive the wheel parameter-chassis motion relationship. MATLAB R2023b-ADAMS 2024 co-simulations show the chassis maintains attitude stability under S-shaped curve, circular curve, and in-situ rotation; Qualisys 3D motion capture experiments confirm its stable attitude in omnidirectional movement.
This paper proposes a nonlinear and robust State-Dependent Riccati Equation (SDRE) combined with H∞ control architecture for brake- by-wire systems, specifically designed to handle severe tire-road friction variations and μ-split scenarios. The primary objective is to maximize deceleration capabilities while rigorously maintaining yaw stability, trajectory tracking, and passenger comfort through jerk limitation. Situated within the domain of active safety, this research addresses robustness against real-world uncertainties by utilizing a high-fidelity 14-degree-of-freedom vehicle model that accounts for longitudinal, lateral, and yaw dynamics, suspension-induced pitch and roll effects, and nonlinear tire behavior with explicit load transfer. To ensure near-optimal slip tracking under variable surface conditions, the system employs online friction estimation via Extended and Unscented Kalman Filters (EKF/UKF) fusing wheel and IMU data to adaptively adjust slip targets. The control strategy is bifurcated: the SDRE component manages dominant nonlinearities through state-dependent gains to prevent wheel lock-up, while the H∞ component provides robust disturbance rejection against parametric uncertainties such as mass variations and sensor noise. Control efforts are distributed via a Quadratic Programming (QP) torque allocator featuring anti-windup mechanisms and explicit saturation handling to compensate for lateral drift during μ-split braking. Validation is conducted through a Model- in-the-Loop (MIL) to Software-in-the-Loop (SIL) pipeline using scenarios including wet surfaces and panic braking. Simulation results demonstrate enhanced yaw stability and controlled deceleration profiles compared to conventional baselines, ensuring computational feasibility for automotive Electronic Control Units (ECUs).
This paper, for the first time, applies the Divine Religions Algorithm (DRA) to three-dimensional UAV path planning. Targeting the complex terrain of urban-mountain mixed environments, we propose a novel method that incorporates multiple enhancements, including A* initialization, single-point disturbance mutation, and adaptive weighting. First, the A* algorithm is employed to generate high-quality initial paths, serving as the skeleton of the population. Innovative mechanisms such as terrain-adaptive disturbances and dynamic weight adjustment are integrated to achieve both efficiency and robustness in path optimization. Comparative experiments with Genetic Algorithm (GA) and Crowned Porcupine Optimization (CPO) show that the improved DRA algorithm exhibits significant advantages in terms of path length, safety margin, average altitude variation, average turning angle, and overall cost function. It consistently obtains superior paths and achieves faster convergence. The results demonstrate that the proposed approach provides an efficient, adaptive, and practical intelligent optimization tool for UAV path planning in urban-mountain mixed or similarly complex environments, offering promising prospects for engineering applications.
According to the working characteristics of the tire changer, the movement characteristics of its rim clamping mechanism are analyzed, and the complex movement structure is abstracted and simplified into four identical six-bar mechanism subunits. One of the subunits is taken as the research object, and the mathematical model of kinematic analysis is established. Using MATLAB software to simulate and analyze the motion law of each component, the mechanical characteristics of the component are analyzed. The optimization of the design parameters of the “six-bar mechanism subunit” is realized, the rim clamping mechanism becomes more stable, and the clamping force follows the diameter of the rim more closely.
To address the limitations of the traditional A* algorithm in lane-level navigation, we propose an autonomous vehicle path planning algorithm based on high-precision maps and an improved A* algorithm to ensure effective application in complex traffic environments. We construct a hierarchical high-precision map based on the Lanelet2 framework to achieve structured modeling of complex road environments. To address the adaptability issues of the A* algorithm in lane-level navigation, we propose optimization schemes, including heuristic function improvements, path segment division, and target point validity verification, to ensure that vehicles can autonomously change lanes on multi-lane roads. By combining dynamic programming (DP) and quadratic programming (QP), we ensure the safety and smoothness of the path. Simulation results demonstrate that the optimized algorithm enables smooth stopping and starting at traffic lights in structured road environments and autonomous lane changes on multi-lane roads. Compared to using DP alone, QP provides smoother and safer driving paths and exhibits superior obstacle avoidance performance in speed planning. This method effectively ensures the rationality of path planning in complex road environments while strictly adhering to traffic rules, thereby enhancing the safety and reliability of path planning.
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