Robust Lateral Stabilization Control of In-Wheel-Motor-Driven Mobile Robots via Active Disturbance Suppression Approach.

Due to the praiseworthy maneuverability and actuation flexibility, the in-wheel-motor-driven mobile robots (IWMD-MR) are widely employed in various industrial fields. However, the active estimation and rejection of unknown disturbances/uncertainties remain a tough work for formulating a stable lateral motion controller. To address the challenge, this paper proposes a robust lateral stabilization control (RLSC) scheme for the developed IWMD-MR by designing an active disturbance suppression mechanism.

Coupled fractional-order sliding mode control and obstacle avoidance of a four-wheeled steerable mobile robot.

Recently, four-wheeled steerable mobile robots (FSMR) have attracted increasing attention in industrial fields, however the collision-free trajectory tracking control is still challenging in dynamic environments. This paper studies a new coupled fractional-order sliding mode control (CFSMC) and obstacle avoidance scheme, which has superior capacities of providing more control flexibilities and achieving high-accuracy. Instead of exploring traditional integer-order solutions, novel fractional-order sliding surfaces are proposed to handle the nonlinear interconnected states in a coupled structure.

Reliable and Fast Localization in Ambiguous Environments Using Ambiguity Grid Map.

In real-world robotic navigation, some ambiguous environments contain symmetrical or featureless areas that may cause the perceptual aliasing of external sensors. As a result of that, the uncorrected localization errors will accumulate during the localization process, which imposes difficulties to locate a robot in such a situation. Using the ambiguity grid map (AGM), we address this problem by proposing a novel probabilistic localization method, referred to as AGM-based adaptive Monte Carlo localization.