Mobile robots are expected to traverse on unstructured terrain, especially uneven terrain, or to climb obstacles or slopes. This paper analyzes one such passively–actively transformable mobile robot that is principally aimed at the above issue. A passive locomotion traverses on a rough and flat terrain; an active reconfiguration with an active suspension. This paper investigates the lateral stability of this mobile robot when it reconfigures itself to adjust its roll angle with the active suspension. The principles and configurations of the robot and its active suspension are presented. To analyze the effects of the suspensions’ inputs on robot stability, a mathematic model of the robot on side slopes is presented. Based on the evaluation method of the stability pyramid theory, an analytical expression representing the relationship between the input of the active suspension (linear actuator length) and stability evaluation index on transverse slopes is obtained. The results show that there is an increase in both the lateral stability and minimum lateral tip-over angle under different ground clearances when adjusting the active inputs. Furthermore, the models presented here provide theoretical references and optimization directions for the design and control of mobile robots with adjustable suspensions.

Lateral overturns are the most frequent fatal accidents involving tractors. A tractor being able to travel safely on uneven or sloped terrain is still an open field of investigation. The design concept of a four-wheel-drive tractor that can traverse hilly and mountainous areas is described. The tractor’s locomotion system can actively adjust its roll angle by using the attitude adjustment mechanisms equipped on the rear wheels. With double quadrangle mechanisms, the front axle can cooperate with the rear axle to adjust this tractor’s attitude. This tractor can also level its body, steer, and transmit power. The principles and configurations of the two axles are presented. A mathematics/mechanical model of a tractor on lateral slopes was developed. This model considers the relationships of the ground supporting forces when the tractor adjusts its roll angle. Combining the model of specific attitude adjustment mechanisms and the above mechanics model, the lateral stability analysis associated with the active input of the attitude adjustment mechanism is conducted. The reliability of the proposed model is discussed based on a comparison of slope traversing experiments and numerical simulations. This designed tractor has potential application in the fields of hilly and mountainous terrains. The results show that posture/configuration adjustment is a positive way to enhance tractor lateral overturn stability.

A Highway Intelligent Space System (HISS) is proposed to study vehicle environment perception in this paper. The nature of HISS is that a space sensors system using laser, ultrasonic or radar sensors are installed in a highway environment and communication technology is used to realize the information exchange between the HISS server and vehicles, which provides vehicles with the surrounding road information. Considering the high-speed feature of vehicles on highways, when vehicles will be passing a road ahead that is prone to accidents, the vehicle driving state should be predicted to ensure drivers have road environment perception information in advance, thereby ensuring vehicle driving safety and stability. In order to verify the accuracy and feasibility of the HISS, a traditional vehicle-mounted sensor system for environment perception is used to obtain the relative driving state. Furthermore, an inter-vehicle dynamics model is built and model predictive control approach is used to predict the driving state in the following period. Finally, the simulation results shows that using the HISS for environment perception can arrive at the same results detected by a traditional vehicle-mounted sensors system. Meanwhile, we can further draw the conclusion that using HISS to realize vehicle environment perception can ensure system stability, thereby demonstrating the method’s feasibility.

Variable-diameter wheels balance the high mobility and limited volume of a planetary rover. Moreover, these wheels allow a rover to adjust its body attitude to adapt to rough terrains. These functions are achieved through the expansion–retraction motion of the variable-diameter mechanisms in the wheels. Thus, the traditional wheel design focuses on these mechanisms. To further facilitate its application, we propose a new concept variable-diameter wheel that considers the mechanism characteristics and wheel performances. This new wheel configuration is presented along with the corresponding transmission system, design, and analysis methods. Kinematic equations of the mechanism were established and then applied to synthesize the wheel dimensions. The load–deflection relationship of the wheels was analytically derived by developing a modified pseudo-rigid-body model (PRBM). Finite element analysis (FEA) simulations were performed to validate the design and analysis. In conclusion, the proposed novel wheel is extremely beneficial for rough-terrain locomotion systems. Furthermore, the design and analysis approaches used in this study are applicable for other expandable wheels.

Intelligent space was established in the highway area in order to detect vehicles and their state information using multi-sensor information fusion. A vehicle location and speed detection method with fixed cameras was proposed by applying Pin-hole imaging model and the principle of Coordinate Transformation; vehicle state information of multi-sensors was fused by the decision method of basic belief function, on the basis of D-S evidence theory in feature-level fusion. Finally, a data acquisition experiment of vehicle state information was carried out by using multi-sensor combination of fixed cameras and ground magnetic induction loops. Then, the collected vehicle state information of these two kinds of sensors was fused and analyzed. Results showed that the accuracy of this fusion method is 5% higher than the fixed cameras. Therefore, the information fusion can reduce the uncertainty of each sensor effectively and improve the detection accuracy of the vehicle state information in highway intelligent space.

Lane detection is a crucial issue for advanced driving assistance systems (ADAS) as well as for autonomous vehicle guidance functions and it is required to have high real-time performance and reliability to avoid lane departure. Taking the curve road as the main interest field, this paper presents a 3D curve lane model to detect, track and reconstruct real roads based on stereovision. The stereovision algorithm defines the 3D curve lane as the vertical and horizontal clothoid, which allows elimination of the common assumption: rectilinear lane, flat road or constant pitch angle. To accurately detect and match the curve lane, this paper proposes an improved real-time ROI setup algorithm. The successive detection results are used to estimate the lane model parameters through Kalman filtering. The experiments show that the algorithm proposed has good real-time performance and robustness.