Purpose: The purpose of this paper is to evaluate the locomotion performance of all‐terrain rovers employing rocker‐type suspension system.Design/methodology/approach: In this paper, a robot with advanced mobility features is presented and its locomotion performance is evaluated, following an analytical approach via extensive simulations. The vehicle features an independently controlled four‐wheel‐drive/4‐wheel‐steer architecture and it also employs a passive rocker‐type suspension system that improves the ability to traverse uneven terrain. An overview of modeling techniques for rover‐like vehicles is introduced. First, a method for formulating a kinematic model of an articulated vehicle is presented. Next, a method for expressing a quasi‐static model of forces acting on the robot is described. A modified rocker‐type suspension is also proposed that enables wheel camber change, allowing each wheel to keep an upright posture as the suspension conforms to ground unevenness.Findings: The proposed models can be used to assess the locomotion performance of a mobile robot on rough‐terrain for design, control and path planning purposes. The advantage of the rocker‐type suspension over conventional spring‐type counterparts is demonstrated. The variable camber suspension is shown to be effective in improving a robot's traction and climbing ability.Research limitations/implications: The paper can be of great value when studying and optimizing the locomotion performance of mobile robots on rough terrain. These models can be used as a basis for advanced design, control and motion planning.Originality/value: The paper describes an analytical approach for the study of the mobility characteristics of vehicles endowed with articulated suspension systems. A variable camber mechanism is also presented.

Sailing navigation is an activity that requires acquiring and processing information from the surrounding environment. The advancement of technology has enabled sailboats to have an increasing number of onboard sensors that make sailing more user-friendly. However, data provided by these sensors are still visualized on 2D digital displays that imitate traditional analog interfaces. Although these displays are strategically placed on the sailboat, the user needs to divert attention from the primary navigation task to look at them, thus spending a significant amount of cognitive resources. AR-based technologies have the potential to overcome these limitations by displaying information registered in the real environment, but there are no studies in the literature for validating the effectiveness of this technology in the field of sailing. Thus, we designed a head-mounted display AR-based interface to assist users in monitoring wind data to avoid user diversion from the primary task of sailing. We conducted a user study involving 45 participants in an Immersive Virtual Reality simulated environment. We collected objective and subjective measures to compare the AR-based interface with a traditional data visualization system. The AR-based interface outperformed the traditional data visualization system regarding reaction time, cognitive load, system usability, and user experience.

A long range visual perception system is presented based on a multi-baseline stereo frame. The system is intended to be used onboard an autonomous vehicle operating in natural settings, such as an agricultural environment, to perform 3D scene reconstruction and segmentation tasks. First, the multi-baseline stereo sensor and the associated processing algorithms are described; then, a self-learning ground classifier is applied to segment the scene into ground and non-ground regions, using geometric features, without any a priori assumption on the terrain characteristics. Experimental results obtained with an off-road vehicle operating in an agricultural test field are presented to validate the proposed approach. It is shown that the use of a multi-baseline stereo frame allows for accurate reconstruction and scene segmentation at a wide range of viewing distances, thus increasing the overall flexibility and reliability of the perception system.