Search Results (17)

This paper presents a mathematical modeling-based vision-guided triple-loop control method for lane tracking of an underactuated bicycle robot. To describe the coupling between lateral balance and path tracking, a reaction-wheel-based inverted-pendulum model is established using the Lagrange formulation. Based on the linearized dynamics, the transfer function between the flywheel rotational speed and the motor torque is derived, providing a mathematical basis for designing the gain-scheduled triple-loop PID controller. To generate continuous control inputs under practical visual disturbances, an improved Hough transform, a near-field multi-layer sliding window detector, and a multi-scenario finite-state-machine strategy are incorporated for lateral deviation estimation and path reconstruction. A cascaded smoothing filter is further introduced to reduce high-frequency command fluctuations and improve the closed-loop control response. Real-vehicle experiments on an STM32F407-based underactuated bicycle robot demonstrate that the proposed framework achieves stable dynamic balance and robust lane tracking. Compared with a conventional Hough-transform and sliding window method, the lateral RMSE is reduced by 40.2%, 39.85%, and 32.35% in straight, left-turn, and right-turn scenarios, respectively. Full article

Modular Mobile Robotic Systems (MMRSs) require simulation tools capable of supporting distributed control architectures, dynamic reconfiguration, and scalable experimentation. This work evaluates three complementary simulation strategies for a homogeneous MMRS composed of autonomous Two-Wheel Inverted Pendulum (TWIP) modules: (i) Webots, selected for rapid prototyping through its integrated GUI; (ii) Pinocchio, paired with the Jiminy simulator to enable modern rigid-body dynamics and control-oriented modeling; and (iii) PyBullet, chosen for programmatic flexibility and reinforcement learning (RL) compatibility. A minimal and controlled benchmark scenario was implemented across all platforms to isolate core simulation characteristics: two differentially driven robots were coupled using the most appropriate mechanism available in each environment and simulated for 1000 steps in headless mode while monitoring CPU usage, memory consumption, and execution time. In addition, a feature-based analysis focused on MMRS-relevant requirements, including dynamic reconfiguration, multi-agent scalability, and suitability for RL workflows. Full article

Two-wheeled self-balancing robots exhibit nonlinear and inherently unstable dynamics due to their inverted-pendulum structure, making control design challenging under terrain variations and external disturbances. This paper proposes a hybrid master–slave fuzzy cascade controller with an additional wheel-synchronization loop to improve tracking performance and robustness. The architecture combines a master velocity PI loop with fuzzy-tuned integral action and a slave balance PD loop with fuzzy proportional control, while a differential synchronization mechanism compensates for motor mismatches without affecting the global balance dynamics. Local stability is analyzed through linearization and equivalent gain approximation within a sector-bounded framework. Experimental validation was conducted on an ESP32-based TWSBR under flat, uphill, and downhill conditions at reference velocities of $0.15$, $0.20$, and $0.30{\displaystyle \frac{\mathrm{m}}{\mathrm{s}}}$, including payload tests with additional masses of $0.279$ and $0.375\mathrm{kg}$. For each scenario, 30 independent trials were performed to compute the reported metrics. Compared with a conventional PID controller, the proposed strategy reduced the flat-terrain velocity RMSE from $0.0108$ to $0.0057{\displaystyle \frac{\mathrm{m}}{\mathrm{s}}}$, while also improving angular stabilization and robustness under slope and payload disturbances. Full article

Wheeled inverted-pendulum robots with movable upper structures and variable payloads exhibit configuration-dependent equilibrium drift and payload-dependent dynamic variation, which complicate balancing control. This paper proposes a gain-scheduled controller–observer framework for payload-adaptive balancing of such a robot. First, the multi-body system is reduced to a control-oriented equivalent inverted-pendulum model through center-of-mass lumping, from which a parameter-varying linearized model is established. On this basis, an H∞ state-feedback controller with input constraints is synthesized in a linear matrix inequality (LMI) framework, and an augmented-state observer is designed to estimate the residual equilibrium offset induced by payload variation. To improve robustness over the operating range, the frozen-point design is extended to a sampled-model multi-model synthesis framework, and gain scheduling is implemented with respect to the measurable arm angle. Nonlinear Simscape simulations show that the proposed method can recover balance at representative fixed operating points, compensate effectively for load-induced equilibrium drifts, and preserve stable balancing performance under slow arm-angle variation. Quantitative comparisons with an LQR baseline further support the effectiveness of the proposed framework for payload-adaptive balancing control. Full article

This paper addresses the problem of stabilizing an inverted pendulum actuated by a reaction wheel, a system relevant for robotic balancing platforms and aerospace applications. The study compares several state-space representations of the system and examines their implications for controller synthesis and parameter identification. A unified nonlinear model formulation is introduced, enabling a structural Lyapunov-based robustness analysis that reveals how variations in the gravitational gain affect closed-loop stability. Control strategies based on pole placement and Linear Quadratic Regulator (LQR) design are implemented and compared across the different representations. The analysis highlights a robustness–fidelity trade-off between model complexity and sensitivity to parameter uncertainty, providing insight that extends beyond the specific laboratory setup. Theoretical results are validated on a real laboratory platform. The controllers are evaluated in both upright and downward equilibrium configurations, and the influence of parameter shifts is assessed experimentally using global identification and performance indices. The work offers general modeling and robustness guidelines for reaction-wheel-based stabilization systems and related underactuated nonlinear mechanisms. Full article

A wheeled–legged robot has the advantage of stable and agile movement on flat ground and an excellent ability to overcome obstacles. However, when faced with a narrow footprint, there is a limit to its ability to move. We developed the control moment gyroscope (CMG) unicycle–legged robot to solve this problem. A scissored pair of CMGs was applied to control the roll balance, and the pitch balance was modeled as a double-inverted pendulum. We performed Linear Quadratic Regulator (LQR) control and model predictive control (MPC) in a system in which the control systems in the roll and pitch directions were separated. We also devised a method for controlling the rotation of the robot in the yaw direction using torque generated by the CMG, and the performance of these controllers was verified in the Gazebo simulator. In addition, forward driving control was performed to verify mobility, which is the main advantage of the wheeled–legged robot; it was confirmed that this control enabled the robot to pass through a narrow space of 0.15 m. Before implementing the verified controllers in the real world, we built a CMG test platform and confirmed that balancing control was maintained within $\pm 1^{\circ }$. Full article

Sustainability and resource optimization have spurred interest in giving a second life to used equipment, often discarded after limited use. Within this framework, we conducted a multidisciplinary, final-year engineering project to explore the reverse engineering and repurposing of commercial hoverboards for an auto-stabilizing, modular robotic platform, with emphasis on medical applications such as transporting medication. The innovation lies in recycling hoverboards to develop a teleoperated, stabilized base that can accommodate additional modules—for instance, a multifunctional arm or a transport shelf—akin to existing commercial robots. Our methodology involves disassembling and reprogramming the hoverboard’s motor controllers and sensors to maintain horizontal stability. Control is realized through the sensor fusion of accelerometer and gyroscope data, processed by a Kalman filter and implemented in a Proportional-Integral-Derivative (PID) loop. A user-friendly Human-Machine Interface (HMI), hosted on an ESP32 microcontroller, enables remote operation and monitoring. Experimental results show that the platform autonomously balances, carries payloads, and achieves high energy efficiency, highlighting its potential as a sustainable and versatile solution in modular robotic applications. Full article

Jumping is a fundamental capability for wheeled-bipedal robots (WBRs) navigating unstructured terrains, with jump height and stability serving as indicators of the robot’s environmental adaptability. However, existing trajectory planning methods demand high output capacity from the joints and fail to balance computational load with trajectory tracking performance. This limitation hinders most robots from experimental validation. To address these challenges, this study presents an optimized virtual model, trajectory planning strategy, and control method. These solutions enhance both the height and stability of jumps while ensuring real-time execution on physical robots. Firstly, inspired by the human jumping mechanism, a Nonlinear Wheel-Spring-Loaded Inverted Pendulum (NW-SLIP) model was originally proposed as the virtual model for trajectory planning. The jump height is increased by 3.4 times compared to the linear spring model. Then, cost functions are established based on this virtual model, and the trajectory for each stage is iteratively optimized using Quadratic Programming (QP) and a bisection method. This leads to a 21.5% increase in the maximum jump height while reducing the peak joint torque by 14% at the same height. This significantly eases execution and enhances the robot’s trajectory-tracking ability. Subsequently, a leg statics model is introduced alongside the kinematics model to map the relationship between the virtual model and joint space. This approach improves trajectory tracking performance while circumventing the intricate calculation of the dynamics model, thereby enhancing jump consistency and stability. Finally, the proposed trajectory planning and jump control method is validated through both simulations and real-world experiments, demonstrating its feasibility and effectiveness in practical robotic applications. Full article

When a two-wheeled inverted pendulum (TWIP) robot vehicle travels on slippery roads, the occurrence of wheel slip extremely threatens its postural stability owing to the loss of wheel traction. If a severe wheel slip happens between the driving wheels and contact surfaces, no control techniques can guarantee the driving performance and stability of the TWIP robots in the absence of an extra wheel slip control strategy. In this paper, a TWIP-compatible countermeasure against the wheel slip phenomena is investigated for enhancing the reliability of the vehicle and the robustness of the motion control performance on low-frictional surfaces. To this end, we propose a balancing-prioritized anti-slip control method based on the maximum transmissible torque estimation, which is activated only when a wheel slip is detected by the acceleration slip indicator utilizing accessible data from the IMU and wheel encoders. It is proved that the TWIP vehicles applying the proposed method can successfully cope with low frictional surfaces while maintaining postural stability. Finally, comparative simulations and experiments demonstrate the effectiveness and feasibility of the proposed scheme. Full article

A proposed optimized model for the trajectory tracking control of a wheeled inverted pendulum robot (WIPR) system is presented in this study, which addresses the problem of poor trajectory tracking performance in the presence of unknown disturbances due to the nonlinear and underactuated characteristics of the system. First, a kinematic controller was used to track a reference trajectory and generate a control law that specifies the desired forward and rotation speeds of the system. Next, a nonlinear disturbance observer (NDO) was designed to enhance the system’s robustness to external disturbances and improve its tracking performance. Then, the coupled system state variables were decoupled into two subsystems: a forward rotation subsystem and a tilt angle velocity subsystem. An improved hierarchical sliding mode controller was designed to control these subsystems separately. Finally, simulation experiments were conducted to compare the proposed method with a common sliding mode control approach. The simulation results demonstrate that the proposed method achieves better tracking performance in the presence of unknown disturbances. Full article

This paper considers the balance control problems of a configurable inverted pendulum with an omni-directional wheeled mobile robot. The system consists of two parts. One is an inverted pendulum, and another one is an omni-directional wheeled mobile robot. The system can be configured as a rotary inverted pendulum or a spherical inverted pendulum. The objective is to control the omni-directional wheeled mobile robot to provide translational force on the plane to balance the spherical inverted pendulum and to provide the moment to balance the rotary inverted pendulum. Detailed dynamic models of these two systems are derived for the control strategy design and simulation studies. Stabilizing controllers based on the second-order sliding mode control are designed for both systems. The closed-loop stability is proved based on the passivity properties. The proposed control schemes can guarantee semi-globally asymptotical stability over the upper-half plane. In addition, the conventional sliding mode controllers proposed in our previous work and Linear-Quadratic Regulator (LQR) controllers based on the linearized system models about its upright equilibrium point are also used for performance comparison. The effectiveness of the control strategies is investigated and verified using simulation and experimental studies. In the simulation studies, different sources of uncertainty and disturbance are investigated. It is shown that the second-order sliding mode control outperforms the conventional sliding mode control and LQR control without any uncertainty and disturbance. For robustness to the matched disturbance, the simulation results show that the second-order sliding mode controller has a less significant steady-state oscillation in the pendulum’s angular displacement than other controllers. The simulation results also show that only the second-order sliding mode controller can stabilize the system with a significant initial deviation from the pendulum’s upright position. Finally, the experimental results demonstrate that second-order sliding mode control outperforms conventional sliding mode control and LQR control. Full article

This paper proposes a method to solve the problem of localization and mapping of a two-wheeled inverted pendulum (TWIP) robot on approximately flat ground using a Lidar–IMU–Odometer system. When TWIP is in motion, it is constrained by the ground and suffers from motion disturbances caused by rough terrain or motion shaking. Combining the motion characteristics of TWIP, this paper proposes a framework for localization consisting of a Lidar-IMU-Odometer system. This system formulates a factor graph with five types of factors, thereby coupling relative and absolute measurements from different sensors (including ground constraints) into the system. Moreover, we analyze the constraint dimension of each factor according to the motion characteristics of TWIP and propose a new nonholonomic constraint factor for the odometry pre-integration constraint and ground constraint factor in order to add them naturally to the factor graph with the robot state node on SE(3). Meanwhile, we calculate the uncertainty of each constraint. Utilizing such a nonholonomic constraint factor, a complete lidar–IMU–odometry-based motion estimation system for TWIP is developed via smoothing and mapping. Indoor and outdoor experiments show that our method has better accuracy for two-wheeled inverted pendulum robots. Full article

It is difficult to realize the stable control of a wheeled biped robot (WBR), as it is an underactuated nonlinear system. To improve the balance and dynamic locomotion capabilities of a WBR, a decoupled control framework is proposed. First, the WBR is decoupled into a variable-length wheeled inverted pendulum and a five-link multi-rigid body system. Then, for the above two simplified models, a time-varying linear quadratic regulator and a model predictive controller are designed, respectively. In addition, in order to improve the accuracy of the feedback information of the robot, the Kalman filter is used to optimally estimate the system state. The control framework can enable the WBR to realize changing height, resisting external disturbances, velocity tracking and jumping. The results obtained by simulations and physical experiments verify the effectiveness of the framework. Full article

This paper develops a decoupled multi-loop control for a two-wheeled inverted pendulum (TWIP) robot that can assist user’s with walking. The TWIP robot is equipped with two wheels driven by electrical motors. We derive the system’s transfer function and design a robust loop-shaping controller to balance the system. The simulation and experimental results show that the TWIP system can be balanced but might experience velocity drifts because its balancing point is affected by model variations and disturbances. Therefore, we propose a multi-loop control layout consisting of a velocity loop and a position loop for the TWIP robot. The velocity loop can adjust the balancing point in real-time and regulate the forward velocity, while the position loop can achieve position tracking. For walking assistance, we design a decoupled control structure that transfers the linear and rotational motions of the robot to the commands of two parallel motors. We implement the designed controllers for simulation and experiments and show that the TWIP system employing the proposed decoupled multi-loop control can provide satisfactory responses when assisting with walking. Full article

This work presents the realization of a complicated stabilization problem for a three inverted pendulum links-based mobile robot. The actuators of the mobile robot are direct current motors that have tachometer couplings to measure both the position and speed of the wheels and links. Using direct measurements under load and analyzing the deceleration curve, the motor parameters are determined experimentally. A mathematical model of the robot is obtained via the Euler–Lagrange equations. Next, the nonlinear model is linearized and discretized. Based on this discrete LTI model, an optimal controller is designed. The states and disturbances are estimated using a robust detector. Both the controller and detector are implemented in the robot processor. Numerical simulations and experimental tests show a good performance of the controller despite the presence of disturbances. Full article