This paper proposes a new turning theory for spherical robots, which better describes the turning mechanism of spherical robots under turning constraints, using a pendulum-driven spherical robot as an example. Compared to the previous turning theory, the new theory shows greater alignment with real-world data, especially at high speeds. Based on this new turning theory, we have constructed and optimized a new kinematic model and used this model to design a trajectory tracking algorithm that remains reliable even at high speeds. Physical experiments demonstrate that the new algorithm significantly improves trajectory tracking accuracy at high speeds. Through enhancements to the trajectory tracking algorithm, this study improves the autonomous cruising speed of spherical robots.

This article proposes an adaptive and robust terrain classification control algorithm for a pendulum-driven spherical robot, aiming to solve the problem of insufficient control accuracy caused by using the same controller for different terrains. The common terrains are classified into three categories, and a terrain classification dataset is established based on the vibration signal of the robot. Using LightGBM, combined with the feature window and window voter algorithm proposed in this article, the terrain classification results are corresponded with three proposed controllers. Physical experiment results show that the proposed classification control algorithm can work stably in different terrains, guiding the spherical robot to select the optimal controller to improve its motion performance.

Path planning is a crucial module in motion planning for autonomous driving, aiming at generating kinematically feasible and collision-free paths. Furthermore, the smoothness of generated path is significant for passengers’ comfortable feelings. In this paper, we propose an improved quadratic programming approach that generates optimal paths in urban structure scenarios with the Frenét frame, taking the cost of the path curvature into consideration explicitly. The proposed second-order Taylor-expansion estimation of the path curvature with the lateral spatial parameters can reflect the actual change of path curvature. Various simulated scenarios verify the effectiveness of our proposed method and the improvement of path quality by adding the curvature objective in the optimization procedure. The source code is released as an open-source package for the community.

In this paper, a fuzzy PID controller based on yaw angle prediction is applied to design an attitude controller for a spherical rolling robot. The robot consists of a 2-DOF pendulum located inside a spherical shell with freedom to rotate about the transversal and longitudinal axis. The proposed controller allows the robot to autonomously change its parameters to adapt to different environments based on current state. The past researches on the motion of spherical robots mostly focused on simulation or ideal experimental environment. But in this paper, a physical system is built and experiments are carried out to demonstrate the effectiveness, robustness and adaptability of the controller.

As a wheel traction motor used for electric vehicles (EVs), due to the requirement of high power/torque density and the poor working condition, it is more prone to cause severe inter-turn short circuit (ITSC) faults. In this paper, the ITSC faults characteristics of a permanent magnet synchronous machine (PMSM) used for wheel traction motors in EVs are deeply and comprehensively researched. The influence of fault intensity on machine's parameters and performance are researched at different fault resistances through finite element method (FEM). Besides, factors that affect the amplitude of short circuit current are researched by mathematic formula and simulation, including load state, rotation speed, fault position and branch inductance. Then, the loss and thermal characteristics of the PMSM under different conditions are analyzed. In the last, experiments are conducted to validate the simulation results.