To travel in the uneven and multi-obstacle terrain autonomously, an unmanned reverse tricycle vehicle, which mainly includes the steering, active tilting and driving actuators, is designed. A kinematic modeling framework incorporates terrain-induced camber, pitch, and tilting angles to characterize the vehicle’s dynamic behavior. The analytical investigation focuses on caster angle optimization and demonstrates how a multi-link parallelogram chassis architecture achieves kinematic decoupling between steering and tilting functions. To validate the potential of travelling in uneven terrain, the strait forward traveling across the road bank with near ’0’ inclination, active tilting assistant turning on the level surface, and the challenging counter-gradient slope turning experiments are carried. Experimental validation encompasses three critical scenarios: straight line forward traversal across road bank with near-zero lateral inclination, active tilt-assisted turning on planar surfaces, and counter-gradient slope turning. These trials substantiate the vehicle’s capability to maintain stability while executing complex maneuvers across uneven terrain.

In this study, we develop a methodology to evaluate and benchmark the European Ground Motion Service (EGMS) products. Our approach integrates Global Navigation Satellite Systems (GNSS) measurements and measurements at and around corner reflectors (CRs), targeting the three product levels of the EGMS. We employ statistical tests to identify significant differences in the comparisons, focusing on time series, velocity estimation, and geopositioning. The study applies this practical methodology to evaluate the first EGMS product from 2015 and 2021 over various European test sites with significant surface deformation. The results consistently demonstrate a solid time series and velocity correlation between EGMS and GNSS at the tested sites, with, e.g., most of the differences between velocities being below 2 mm/year. This methodology, implemented in Python notebooks, ensures reproducible results and allows for validating the EGMS over other locations.

Rigid robotic arms have strong load capacity and mature control schemes, but they are often not suitable for working in narrow spaces with multiple obstacles. Flexible robotic arms can bend more freely, but they have weaker load capacity and are not suitable for fine manipulation. In view of this, inspired by the biological structure of the Nycticorax Violaceus, a novel scalable flexible robotic arm for addressing complex spatial fault-tolerant manipulation requirements is proposed in this paper. The robotic arm can be concealed within a shell at the end of a rigid arm without affecting the normal use of the rigid arm. When needed, it can extend from the shell of the rigid arm, serving as a flexible auxiliary operating end attached to the rigid arm base for large curvature bending. This paper presents the structural design of a flexible arm and provides kinematic and dynamic models for the flexible arm extension operation. Through a case study, the kinematic and dynamic models proposed in this paper are validated.

Aiming to intercept non-cooperative targets when global positioning signals are lost or jammed, an Extended State Observer (ESO) based disturbance compensation guidance law for the unmanned surface vessel (USV) is developed. This interception guidance law addresses the scenario where the relative velocity and target maneuver acceleration cannot be directly measured. To circumvent nonlinearities and parameter coupling, a simplified relative interception dynamics model is proposed. Furthermore, an extended state observer is designed to estimate the unmeasured state and the unknown disturbance. Utilizing these estimations, an ESO-based disturbance compensation guidance law (ESO-DCGL) is developed, which can compensate for target maneuvers and track the desired trajectory. Simulation results demonstrate the effectiveness of this guidance law in intercepting non-cooperative targets with high maneuverability.