## 5 Conclusions  
In this paper, a driving force distribution and control strategy for a 6 WD skid-steering EUGV actuated by independent drive wheels is proposed to improve the maneuverability and stability. The key conclusions include the following:  
(1) The architecture of a 6 WD skid-steering EUGV actuated by independent drive wheels was introduced. Focusing on longitudinal, lateral, and yaw motion, a nonlinear vehicle system dynamics model with nine DOFs was established. By using the Magic Formula tire model, the longitudinal and lateral tire forces in pure circumstances were introduced. In order to describe the actual forces of the tire, a dynamics model of the tire in the combined slip circumstances was developed. (2) To improve the maneuverability and stability, a driving force distribution and control strategy was proposed. The control strategy was composed of hierarchical controllers, including an upper layer controller and lower layer controller. In the upper layer controller, the controlled resultant driving force and yaw moment were calculated to control the vehicle motion states to track the desired input by using the integral sliding mode control (ISMC) and proportion-integral-differential (PID) control method. In the lower layer controller, the controlled resultant driving force and yaw moment were realized by distributing the actuator motor's torque. An objective function consisting of the longitudinal tire workload rates and weight factors of the tire was established by considering the inequality constraints, including the actuator constraints, road adhesion constraints, and tire friction circle constraints. The weight factors were composed of the ratio of the tire vertical force considering the vehicle motion conditions and vertical load change of each tire. Based on the active set algorithm, the control distribution method was used to solve the objective function for optimal driving force allocation. (3) Experimental tests were conducted to verify the effectiveness of the proposed control algorithm. Two types of testing scenarios were studied: motion in straight conditions and curved conditions. In addition, the rule-based driving force even allocation method and optimal driving force vectoring distribution method used in the related references were experimented with for comparison. The experimental results demonstrate that the proposed control strategy had excellent performance in vehicle maneuverability and stability. In the curve-tracking condition, compared to Ref2, the longitudinal velocity tracking error and yaw rate tracking error were decreased by 33.9% and 54.5% with the proposed controller in the tracking stabilization stage, respectively. In the future, we will test the experimental platform in different scenarios with different terrains or banks or other more complex situations to test and investigate the robustness of our proposed control method. Conceptualization, H.Z. and H.L. ; investigation, H.Z. ; methodology, H.Z. ; software, H.Z. and X.T. ; validation, H.Z., H.L., and X.T. ; data curation, H.Z. and R.B. ; writing  
Figure 19: Comparison of phase planes. original draft preparation, H.Z. ; writing--review and editing, H.L. and B.Y. ; supervision, H.L. and B.Y. ; project administration, Y.D. ; funding acquisition, H.L. All authors have read and agreed to the published version of the manuscript. This work was supported by the National Key Research and Development Program of China (Nos. 2016 YFD0701401, 2017 YFD0700303 and 2018 YFD0700602); Youth Innovation Promotion Association of the Chinese Academy of Sciences (Grant No. 2017488); Key Supported Project in the Thirteenth Five-year Plan of the Hefei Institutes of Physical Science, Chinese Academy of Sciences (Grant No.KP-2017-35, KP-2017-13 and KP-2019-16); Independent Research Project of the Research Institute of Robotics and Intelligent Manufacturing Innovation, Chinese Academy of Sciences (Grant No. C2018005); and Technological Innovation Project for New Energy and Intelligent Networked Automobile Industry of Anhui Province.