A self-balancing wheel-legged robot provides higher maneuverability and mobility than legged biped robots. For this reason, wheel-legged systems have attracted enormous interest from academia and commercial sectors in recent years. Most of the past works in this field mainly focused on lower body stabilization. Motivated by the human ability to maintain balance in laborious activities by articulating the arm actively, we explore and analyze the active arm control on top of the wheel-legged system to assist in its balance recovery during external pushes and disturbances. This paper presents a control framework to improve the stability and robustness of an underactuated self-balancing wheel-legged robot using its upper limb arm. Furthermore, we use the centroidal moment pivot (CMP) as a key metric to quantitatively evaluate the effect of the active arm usage on the balance stability improvement of the robot in the ROS-Gazebo environment. The difference from the case of nonusage of arm is verified to clarify the impact of the active arm quantitatively. This concept would lead to the wheel-legged biped robot with an active arm for dual purposes, one is for carrying objects, another is for increasing the balance stability. This point is important for future application in a real-world environment with human-robot interactions.INDEX TERMS Wheel-legged robots, wheeled inverted pendulum (WIP), underactuated robots, motion control, balance recovery, stability analysis, disturbance rejection.

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The structure and the operating principle of a Cartesian positioner are expounded. Based on the principle of multi-body system dynamics, the kinematic model of the Cartesian positioner is established. The deformation of each component is analyzed during the fuselage pose alignment by FEA(finite element analysis) . At last the locating error model is established. The locating error model can contribute to the stiffness distribution of components and the structure optimization of the Cartesian positioner.

Purpose This paper aims to present error compensation based on surface reconstruction to improve the positioning accuracy of industrial robots. Design/methodology/approach In previous research, it has been proved that the positioning error of industrial robots is continuous on the two-dimensional manifold of six-joint space. The point cloud generated by positioning error data can be used to fit the continuous surfaces, which makes it possible to apply surface reconstruction on error compensation. The moving least-squares interpolation and the B-spline method are used for the error surface reconstruction. Findings The results of experiments and simulations validate the effectiveness of error compensation by the moving least-squares interpolation and the B-spline method. Practical implications The proposed methods can control the average of compensated positioning error within 0.2 mm, which meets the requirement of a tolerance (±0.5 mm) for fastener hole drilling in aircraft assembly. Originality/value The error surface reconstruction based on the B-spline method has great superiority because fewer sample points are needed to use this method than others while keeping the compensation accuracy at the same level. The control points of the B-spline error surface can be adjusted with measured data, which can be applied for the error prediction in any temperature field.

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