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Keywords = skid-steering

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25 pages, 5451 KiB  
Article
Research on the Stability and Trajectory Tracking Control of a Compound Steering Platform Based on Hierarchical Theory
by Huanqin Feng, Hui Jing, Xiaoyuan Zhang, Bing Kuang, Yifan Song, Chao Wei and Tianwei Qian
Electronics 2025, 14(14), 2836; https://doi.org/10.3390/electronics14142836 - 15 Jul 2025
Viewed by 230
Abstract
Compound steering technology has been extensively adopted in military logistics and related applications, owing to its superior maneuverability and enhanced stability compared to conventional systems. To enhance the steering efficiency and dynamic response of distributed-drive unmanned platforms under low driving torque conditions, this [...] Read more.
Compound steering technology has been extensively adopted in military logistics and related applications, owing to its superior maneuverability and enhanced stability compared to conventional systems. To enhance the steering efficiency and dynamic response of distributed-drive unmanned platforms under low driving torque conditions, this study investigates their unique compound steering system. Specifically, a compound steering dynamics model is established, and a hierarchical stability control strategy, along with a model predictive control-based trajectory tracking algorithm, are innovatively proposed. First, a compound steering platform dynamics model is established by combining the Ackermann steering and skid yaw moment methods. Then, a trajectory tracking controller is designed using model predictive control algorithm. Finally, the additional yaw moment is calculated based on the lateral velocity error and yaw rate error, with stability control allocation performed using a fuzzy control algorithm. Comparative hardware-in-the-loop experiments are conducted for compound steering, Ackermann steering, and skid steering. The experimental results show that the compound steering technology enables unmanned platforms to achieve trajectory tracking tasks with a lower torque, faster speed, and higher efficiency. Full article
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21 pages, 13446 KiB  
Article
Field Evaluation of an Autonomous Mobile Robot for Navigation and Mapping in Forest
by Diego Tiozzo Fasiolo, Lorenzo Scalera, Eleonora Maset and Alessandro Gasparetto
Robotics 2025, 14(7), 89; https://doi.org/10.3390/robotics14070089 - 27 Jun 2025
Viewed by 701
Abstract
This paper presents a mobile robotic system designed for autonomous navigation and forest and tree trait estimation, with a focus on the location of individual trees and the diameter of the trunks. The system integrates light detection and ranging data and images using [...] Read more.
This paper presents a mobile robotic system designed for autonomous navigation and forest and tree trait estimation, with a focus on the location of individual trees and the diameter of the trunks. The system integrates light detection and ranging data and images using a framework based on simultaneous localization and mapping (SLAM) and a deep learning model for trunk segmentation and tree keypoint detection. Field experiments conducted in a wooded area in Udine, Italy, using a skid-steered mobile robot, demonstrate the effectiveness of the system in navigating, while avoiding obstacles (even in cases where the Global Navigation Satellite System signal is not reliable). The results highlight that the proposed robotic system is capable of autonomously generating maps of forests as point clouds with minimal drift thanks to the loop closure strategy integrated in the SLAM algorithm, and estimating tree traits automatically. Full article
(This article belongs to the Special Issue Autonomous Robotics for Exploration)
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18 pages, 3277 KiB  
Article
Neural Networks in the Delayed Teleoperation of a Skid-Steering Robot
by Kleber Patiño, Emanuel Slawiñski, Marco Moran-Armenta, Vicente Mut, Francisco G. Rossomando and Javier Moreno-Valenzuela
Mathematics 2025, 13(13), 2071; https://doi.org/10.3390/math13132071 - 23 Jun 2025
Viewed by 297
Abstract
Bilateral teleoperation of skid-steering mobile robots with time-varying delays presents significant challenges in ensuring accurate leader–follower coupling. This article presents a novel controller for a bilateral teleoperation system composed of a robot manipulator and a skid-steering mobile robot. The proposed controller leverages neural [...] Read more.
Bilateral teleoperation of skid-steering mobile robots with time-varying delays presents significant challenges in ensuring accurate leader–follower coupling. This article presents a novel controller for a bilateral teleoperation system composed of a robot manipulator and a skid-steering mobile robot. The proposed controller leverages neural networks to compensate for ground–robot interactions, uncertain dynamics, and communication delays. The control strategy integrates a shared scheme between damping injection and two neural networks, enhancing the robustness and adaptability of the delayed system. A rigorous theoretical analysis of the closed-loop teleoperation system is provided, establishing conditions of control parameters to ensure stability and convergence of the coordination errors. The proposed method is validated through numerical testing, demonstrating strong agreement between theoretical outcomes and simulation results. Full article
(This article belongs to the Special Issue Advanced Control Theory in Robot System)
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37 pages, 13864 KiB  
Article
LSTM-Enhanced Deep Reinforcement Learning for Robust Trajectory Tracking Control of Skid-Steer Mobile Robots Under Terra-Mechanical Constraints
by Jose Manuel Alcayaga, Oswaldo Anibal Menéndez, Miguel Attilio Torres-Torriti, Juan Pablo Vásconez, Tito Arévalo-Ramirez and Alvaro Javier Prado Romo
Robotics 2025, 14(6), 74; https://doi.org/10.3390/robotics14060074 - 29 May 2025
Viewed by 2228
Abstract
Autonomous navigation in mining environments is challenged by complex wheel–terrain interaction, traction losses caused by slip dynamics, and sensor limitations. This paper investigates the effectiveness of Deep Reinforcement Learning (DRL) techniques for the trajectory tracking control of skid-steer mobile robots operating under terra-mechanical [...] Read more.
Autonomous navigation in mining environments is challenged by complex wheel–terrain interaction, traction losses caused by slip dynamics, and sensor limitations. This paper investigates the effectiveness of Deep Reinforcement Learning (DRL) techniques for the trajectory tracking control of skid-steer mobile robots operating under terra-mechanical constraints. Four state-of-the-art DRL algorithms, i.e., Proximal Policy Optimization (PPO), Deep Deterministic Policy Gradient (DDPG), Twin Delayed DDPG (TD3), and Soft Actor–Critic (SAC), are selected to evaluate their ability to generate stable and adaptive control policies under varying environmental conditions. To address the inherent partial observability in real-world navigation, this study presents an original approach that integrates Long Short-Term Memory (LSTM) networks into DRL-based controllers. This allows control agents to retain and leverage temporal dependencies to infer unobservable system states. The developed agents were trained and tested in simulations and then assessed in field experiments under uneven terrain and dynamic model parameter changes that lead to traction losses in mining environments, targeting various trajectory tracking tasks, including lemniscate and squared-type reference trajectories. This contribution strengthens the robustness and adaptability of DRL agents by enabling better generalization of learned policies compared with their baseline counterparts, while also significantly improving trajectory tracking performance. In particular, LSTM-based controllers achieved reductions in tracking errors of 10%, 74%, 21%, and 37% for DDPG-LSTM, PPO-LSTM, TD3-LSTM, and SAC-LSTM, respectively, compared with their non-recurrent counterparts. Furthermore, DDPG-LSTM and TD3-LSTM reduced their control effort through the total variation in control input by 15% and 20% compared with their respective baseline controllers, respectively. Findings from this work provide valuable insights into the role of memory-augmented reinforcement learning for robust motion control in unstructured and high-uncertainty environments. Full article
(This article belongs to the Section Intelligent Robots and Mechatronics)
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19 pages, 2433 KiB  
Article
Design and Analysis of an MPC-PID-Based Double-Loop Trajectory Tracking Algorithm for Intelligent Sweeping Vehicles
by Zhijun Guo, Mingtian Pang, Shiwen Ye and Yangyang Geng
World Electr. Veh. J. 2025, 16(5), 251; https://doi.org/10.3390/wevj16050251 - 28 Apr 2025
Viewed by 488
Abstract
To enhance the precision and real-time performance of trajectory tracking control in differential-steering intelligent sweeping robots and to improve the adaptability of the control algorithm to errors caused by sensor noise, tire slip, and skid, an MPC-PID (Model Predictive Control–Proportional-Integral-Derivative) dual closed-loop control [...] Read more.
To enhance the precision and real-time performance of trajectory tracking control in differential-steering intelligent sweeping robots and to improve the adaptability of the control algorithm to errors caused by sensor noise, tire slip, and skid, an MPC-PID (Model Predictive Control–Proportional-Integral-Derivative) dual closed-loop control strategy was proposed. This strategy integrates a Kalman filter-based state estimator and a sliding compensation module. Based on the kinematic model of the intelligent sweeping robot, a model predictive controller (MPC) was designed to regulate the vehicle’s pose, while a PID controller was used to adjust the longitudinal speed, forming a dual closed-loop control algorithm. A Kalman filter was employed for state estimation, and a sliding compensation module was introduced to mitigate wheel slip and lateral drift, thereby improving the stability of the control system. Simulation results demonstrated that, compared to traditional MPC control, the maximum lateral deviation, maximum heading angle deviation, and speed response time were reduced by 50.83%, 53.65%, and 7.10%, respectively, during sweeping operations. In normal driving conditions, these parameters were improved by 41.58%, 45.54%, and 24.17%, respectively. Experimental validation on an intelligent sweeper platform demonstrates that the proposed algorithm achieves a 16.48% reduction in maximum lateral deviation and 9.52% faster speed response time compared to traditional MPC, effectively validating its enhanced tracking effectiveness in intelligent cleaning operations. Full article
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25 pages, 3735 KiB  
Article
Modeling and Analysis of the Turning Performance of an Articulated Tracked Vehicle That Considers the Inter-Unit Coupling Forces
by Ningyi Li, Xixia Liu, Hongqian Chen and Yu Zhang
Machines 2025, 13(2), 118; https://doi.org/10.3390/machines13020118 - 4 Feb 2025
Viewed by 856
Abstract
The interactions between ground reaction forces and inter-unit coupling forces add complexity to the study of the turning motion of articulated tracked vehicles (ATVs). To accurately analyze the turning performance of an ATV, this study developed a steady-state steering model that captures the [...] Read more.
The interactions between ground reaction forces and inter-unit coupling forces add complexity to the study of the turning motion of articulated tracked vehicles (ATVs). To accurately analyze the turning performance of an ATV, this study developed a steady-state steering model that captures the effects of load transfer caused by coupling and centrifugal forces. First, based on vehicle kinematics under skidding conditions, formulas that incorporate parameters for the lateral track displacement were derived to calculate the turning radii of the front and rear units. Then, the track traction forces and turning resistance moments were calculated using the shear stress–shear displacement relationship. Finally, a steady-state steering model on firm ground conditions was developed for the vehicle according to mechanical equilibrium conditions, and the model was validated using previously reported data. Analyses of the results revealed that the coupling forces provided the driving moments for the turning motion by the transfer of the centrifugal and ground reaction forces that acted on the front and rear units. During turning, the rear unit had a larger radius than the front unit, and the minimum swept radius of the ATV was dependent upon the radius of the outer track trajectory of the rear unit. Specifically, at a speed of 3.1 m/s and a steering angle of 35°, the vehicle exhibited a minimum outer swept radius of 8.8 m, requiring a turning space equivalent to a 3.1-m-wide road. The required turning space increased as both the steering angle and speed increased. Full article
(This article belongs to the Section Vehicle Engineering)
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30 pages, 3727 KiB  
Article
Tracking Control of a Four-Wheeled Skid-Steered Robot with Slip Compensation and Application of the Drive Unit Model
by Maciej Trojnacki
Electronics 2025, 14(3), 444; https://doi.org/10.3390/electronics14030444 - 22 Jan 2025
Cited by 1 | Viewed by 1689
Abstract
This article focuses on trajectory tracking control of a four-wheeled mobile robot, with non-steered wheels. The issues in terms of robot kinematics are discussed and a dynamics model is derived, which additionally took into account the drive unit model. This paper analyses four [...] Read more.
This article focuses on trajectory tracking control of a four-wheeled mobile robot, with non-steered wheels. The issues in terms of robot kinematics are discussed and a dynamics model is derived, which additionally took into account the drive unit model. This paper analyses four versions of the control system, which take into account the possibility of compensating for wheel slip and non-linearities resulting from the drive unit model. It is assumed that the wheel-slip compensation is based on the measurement of the actual robot’s motion parameters. The linear and angular motion parameters of the robot’s mobile platform are taken into account, which allows for the estimation of the wheel slip velocities. The results of the simulation studies are presented, consisting of the evaluation of individual control system solutions in terms of achieving the highest possible accuracy in executing a prescribed trajectory. Additionally, the impact of the investigated control strategies on electric power demand and electric energy consumption by the robot’s drives is analyzed. In order to quantitatively assess the control system solutions, quality indexes were adopted, focusing on tracking accuracy and energy efficiency. The research results indicate that incorporating wheel-slip compensation into the control system enables high accuracy to be achieved in terms of trajectory tracking. In turn, the use of the drive unit model within the control system leads to an increase in the accuracy of the robot’s wheel movements, which does not ultimately result in an increase in the accuracy of the motion of the robot’s mobile platform due to the slipping of the wheels. It was also observed that improving the trajectory tracking accuracy leads to an increase in the maximum electric power demand and electric energy consumption by the robot’s drives. Full article
(This article belongs to the Section Electrical and Autonomous Vehicles)
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20 pages, 3804 KiB  
Article
Torque Differential-Based Dynamic Modeling, Validation, and Steering Characteristics Analysis of Multi-Axial Skid-Steered Wheeled Vehicle
by Yuzheng Zhu, Shihua Yuan, Xueyuan Li, Ao Li and Xin Gao
Actuators 2025, 14(1), 13; https://doi.org/10.3390/act14010013 - 4 Jan 2025
Viewed by 1232
Abstract
Skid-steered technology has been widely applied to wheeled vehicles due to its advanced pivot steering capabilities and adaptable power transmission systems. To better understand the steering characteristics of skid-steered wheeled vehicles and derive general conclusions, a torque differential-based (TD-based) two-degree-of-freedom (2-DOF) dynamic model [...] Read more.
Skid-steered technology has been widely applied to wheeled vehicles due to its advanced pivot steering capabilities and adaptable power transmission systems. To better understand the steering characteristics of skid-steered wheeled vehicles and derive general conclusions, a torque differential-based (TD-based) two-degree-of-freedom (2-DOF) dynamic model was developed. This model is grounded in the vehicle’s steering mechanism and the single-wheel dynamics model, and a steering radius model based on TD input was established using the concept of the instantaneous center of rotation (ICR). Additionally, an expression for the stability factor was derived, and both the steady-state and transient steering characteristics were analyzed. Finally, the real vehicle tests demonstrated that the TD-based dynamic model responds quickly, maintains high precision, and remains stable across different steering input frequencies. Compared with the SD-based dynamic model, the TD-based dynamic model has a 2.553% higher calculation accuracy for the steering radius, a 6.251% higher comprehensive response accuracy for the steering input, and a response speed advantage of 1.035%. Full article
(This article belongs to the Section Actuators for Surface Vehicles)
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17 pages, 1570 KiB  
Article
Backstepping-Based Nonsingular Terminal Sliding Mode Control for Finite-Time Trajectory Tracking of a Skid-Steer Mobile Robot
by Mulugeta Debebe Teji, Ting Zou and Dinku Seyoum Zeleke
Robotics 2024, 13(12), 180; https://doi.org/10.3390/robotics13120180 - 16 Dec 2024
Cited by 1 | Viewed by 1482
Abstract
Skid-steer mobile robots (SSMRs) are ubiquitous in indoor and outdoor applications. Their accurate trajectory tracking control is quite challenging due to the uncertainties arising from the complex behavior of frictional force, external disturbances, and fluctuations in the instantaneous center of rotation (ICR) during [...] Read more.
Skid-steer mobile robots (SSMRs) are ubiquitous in indoor and outdoor applications. Their accurate trajectory tracking control is quite challenging due to the uncertainties arising from the complex behavior of frictional force, external disturbances, and fluctuations in the instantaneous center of rotation (ICR) during turning maneuvers. These uncertainties directly disturb velocities, hindering the robot from tracking the velocity command. This paper proposes a nonsingular terminal sliding mode control (NTSMC) based on backstepping for a four-wheel SSMR to cope with the aforementioned challenges. The strategy seeks to mitigate the impacts of external disturbances and model uncertainties by developing an adaptive law to estimate the integrated lumped outcome. The finite time stability of the closed-loop system is proven using Lyapunov’s theory. The designed NTSMC input is continuous and avoids noticeable chattering. It was noted in the simulation analysis that the proposed control strategy is strongly robust against disturbance and modeling uncertainties, demonstrating effective trajectory tracking performance in the presence of disturbance and modeling uncertainties. Full article
(This article belongs to the Special Issue Navigation Systems of Autonomous Underwater and Surface Vehicles)
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30 pages, 15218 KiB  
Article
Robust Nonlinear Model Predictive Control for the Trajectory Tracking of Skid-Steer Mobile Manipulators with Wheel–Ground Interactions
by Katherine Aro, Leonardo Guevara, Miguel Torres-Torriti, Felipe Torres and Alvaro Prado
Robotics 2024, 13(12), 171; https://doi.org/10.3390/robotics13120171 - 3 Dec 2024
Cited by 2 | Viewed by 2071
Abstract
This paper presents a robust control strategy for trajectory-tracking control of Skid-Steer Mobile Manipulators (SSMMs) using a Robust Nonlinear Model Predictive Control (R-NMPC) approach that minimises trajectory-tracking errors while overcoming model uncertainties and terra-mechanical disturbances. The proposed strategy is aimed at counteracting the [...] Read more.
This paper presents a robust control strategy for trajectory-tracking control of Skid-Steer Mobile Manipulators (SSMMs) using a Robust Nonlinear Model Predictive Control (R-NMPC) approach that minimises trajectory-tracking errors while overcoming model uncertainties and terra-mechanical disturbances. The proposed strategy is aimed at counteracting the effects of disturbances caused by the slip phenomena through the wheel–terrain contact and bidirectional interactions propagated by mechanical coupling between the SSMM base and arm. These interactions are modelled using a coupled nonlinear dynamic framework that integrates bounded uncertainties for the mobile base and arm joints. The model is developed based on principles of full-body energy balance and link torques. Then, a centralized control architecture integrates a nominal NMPC (disturbance-free) and ancillary controller based on Active Disturbance-Rejection Control (ADRC) to strengthen control robustness, operating the full system dynamics as a single robotic body. While the NMPC strategy is responsible for the trajectory-tracking control task, the ADRC leverages an Extended State Observer (ESO) to quantify the impact of external disturbances. Then, the ADRC is devoted to compensating for external disturbances and uncertainties stemming from the model mismatch between the nominal representation and the actual system response. Simulation and field experiments conducted on an assembled Pioneer 3P-AT base and Katana 6M180 robotic arm under terrain constraints demonstrate the effectiveness of the proposed method. Compared to non-robust controllers, the R-NMPC approach significantly reduced trajectory-tracking errors by 79.5% for mobile bases and 42.3% for robot arms. These results highlight the potential to enhance robust performance and resource efficiency in complex navigation conditions. Full article
(This article belongs to the Section Sensors and Control in Robotics)
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18 pages, 10290 KiB  
Article
Assessment of Hydraulic Oil Properties during Operation of a Mini Loader
by Diego Andrés Duque-Sarmiento and Daysi Alexandra Baño-Morales
Lubricants 2024, 12(9), 320; https://doi.org/10.3390/lubricants12090320 - 17 Sep 2024
Cited by 2 | Viewed by 2321
Abstract
This study employs a rigorous methodology to assess the condition of the hydraulic oil in a recently introduced mini skid-steer loader. The assessment is conducted through laboratory analysis, which adheres to a range of international standards. The objective is to provide accurate insights [...] Read more.
This study employs a rigorous methodology to assess the condition of the hydraulic oil in a recently introduced mini skid-steer loader. The assessment is conducted through laboratory analysis, which adheres to a range of international standards. The objective is to provide accurate insights into the viscosity, particle count, and characterisation of the oil, along with thermographic data. The friction of oil is evaluated at specific time points: 0, 10, 100, 125, and 150 h of operation. This examination offers a comprehensive insight into the alterations in oil characteristics during a pivotal period when machine components are undergoing initial consolidation and abrasion to attain the factory-defined performance thresholds. The principal aim of this research is to provide valuable insights into the wear of oil and hydraulic system components through an in-depth analysis of a range of variables. Moreover, the investigation aims to ascertain the impact of this factor on the temperature elevation of system components and accessories to formulate enhanced technical guidelines for implementation. The main results indicate the presence of particles in the oil, resulting in a cleanliness code of 23/21/13, which exceeds the permissible threshold of 20/18/15 specified in ISO 11171. In addition, hydraulic oil shows a viscosity instability of more than 10% due to moisture absorption, leading to wear of mechanical components composed of iron, nickel, copper, zinc, and silicon. This deterioration is corroborated by thermographic evaluations, which reveal a considerable temperature increase in components such as cylinders and system accessories. Full article
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26 pages, 14424 KiB  
Article
An Integrated Route and Path Planning Strategy for Skid–Steer Mobile Robots in Assisted Harvesting Tasks with Terrain Traversability Constraints
by Ricardo Paul Urvina, César Leonardo Guevara, Juan Pablo Vásconez and Alvaro Javier Prado
Agriculture 2024, 14(8), 1206; https://doi.org/10.3390/agriculture14081206 - 23 Jul 2024
Cited by 10 | Viewed by 2258
Abstract
This article presents a combined route and path planning strategy to guide Skid–Steer Mobile Robots (SSMRs) in scheduled harvest tasks within expansive crop rows with complex terrain conditions. The proposed strategy integrates: (i) a global planning algorithm based on the Traveling Salesman Problem [...] Read more.
This article presents a combined route and path planning strategy to guide Skid–Steer Mobile Robots (SSMRs) in scheduled harvest tasks within expansive crop rows with complex terrain conditions. The proposed strategy integrates: (i) a global planning algorithm based on the Traveling Salesman Problem under the Capacitated Vehicle Routing approach and Optimization Routing (OR-tools from Google) to prioritize harvesting positions by minimum path length, unexplored harvest points, and vehicle payload capacity; and (ii) a local planning strategy using Informed Rapidly-exploring Random Tree (IRRT*) to coordinate scheduled harvesting points while avoiding low-traction terrain obstacles. The global approach generates an ordered queue of harvesting locations, maximizing the crop yield in a workspace map. In the second stage, the IRRT* planner avoids potential obstacles, including farm layout and slippery terrain. The path planning scheme incorporates a traversability model and a motion model of SSMRs to meet kinematic constraints. Experimental results in a generic fruit orchard demonstrate the effectiveness of the proposed strategy. In particular, the IRRT* algorithm outperformed RRT and RRT* with 96.1% and 97.6% smoother paths, respectively. The IRRT* also showed improved navigation efficiency, avoiding obstacles and slippage zones, making it suitable for precision agriculture. Full article
(This article belongs to the Section Agricultural Technology)
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21 pages, 7819 KiB  
Article
Research on the Deviation Correction Control of a Tracked Drilling and Anchoring Robot in a Tunnel Environment
by Chuanwei Wang, Hongwei Ma, Xusheng Xue, Qinghua Mao, Jinquan Song, Rongquan Wang and Qi Liu
Actuators 2024, 13(6), 221; https://doi.org/10.3390/act13060221 - 13 Jun 2024
Cited by 2 | Viewed by 1356
Abstract
In response to the challenges of multiple personnel, heavy support tasks, and high labor intensity in coal mine tunnel drilling and anchoring operations, this study proposes a novel tracked drilling and anchoring robot. The robot is required to maintain alignment with the centerline [...] Read more.
In response to the challenges of multiple personnel, heavy support tasks, and high labor intensity in coal mine tunnel drilling and anchoring operations, this study proposes a novel tracked drilling and anchoring robot. The robot is required to maintain alignment with the centerline of the tunnel during operation. However, owing to the effects of skidding and slipping between the track mechanism and the floor, the precise control of a drilling and anchoring robot in tunnel environments is difficult to achieve. Through an analysis of the body and track mechanisms of the drilling and anchoring robot, a kinematic model reflecting the pose, steering radius, steering curvature, and angular velocity of the drive wheel of the drilling and anchoring robot was established. This facilitated the determination of speed control requirements for the track mechanism under varying driving conditions. Mathematical models were developed to describe the relationships between a tracked drilling and anchoring robot and several key factors in tunnel environments, including the minimum steering space required by the robot, the minimum relative steering radius, the steering angle, and the lateral distance to the sidewalls. Based on these models, deviation-correction control strategies were formulated for the robot, and deviation-correction path planning was completed. In addition, a PID motion controller was developed for the robot, and trajectory-tracking control simulation experiments were conducted. The experimental results indicate that the tracked drilling and anchoring robot achieves precise control of trajectory tracking, with a tracking error of less than 0.004 m in the x-direction from the tunnel centerline and less than 0.001 m in the y-direction. Considering the influence of skidding, the deviation correction control performance test experiments of the tracked drilling and anchoring robot at dy = 0.5 m away from the tunnel centerline were completed. In the experiments, the tracked drilling and anchoring robot exhibited a significant difference in speed between the two sides of the tracks with a track skid rate of 0.22. Although the real-time tracking maximum error in the y-direction from the tunnel centerline was 0.13 m, the final error was 0.003 m, meeting the requirements for position deviation control of the drilling and anchoring robot in tunnel environments. These research findings provide a theoretical basis and technical support for the intelligent control of tracked mobile devices in coal mine tunnels, with significant theoretical and engineering implications. Full article
(This article belongs to the Special Issue Advanced Robots: Design, Control and Application—2nd Edition)
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28 pages, 4680 KiB  
Article
Model-Based Analysis of the Accuracy of Tracking Control and Energy Efficiency of a Six-Wheeled Skid-Steered Robot
by Maciej Trojnacki
Appl. Sci. 2024, 14(6), 2335; https://doi.org/10.3390/app14062335 - 10 Mar 2024
Viewed by 1685
Abstract
This article concerns the modeling and motion control of a mobile robot with six independently driven and non-steered wheels. The main research issue is analyzing the influence of the structure of the control system and wheel track on the control accuracy and energy [...] Read more.
This article concerns the modeling and motion control of a mobile robot with six independently driven and non-steered wheels. The main research issue is analyzing the influence of the structure of the control system and wheel track on the control accuracy and energy efficiency during robot motion on horizontal paved ground. For this purpose, the kinematic relationships for the robot are discussed and a simplified dynamics model for control applications is developed. The robot’s dynamics model takes into account the most important phenomena of the wheel interaction with the paved ground, including slip. In addition, it is supplemented with a model of the robot’s drive units. Two versions of the control system were adopted for analysis, i.e., with the wheels’ controller only and additionally equipped with a pose controller. Simulation studies were carried out for the developed robot dynamics model and the analyzed versions of the control system in order to investigate the influence of the track width of the wheels and the structure of the control system on motion accuracy and energy efficiency. In order to quantitatively compare the results for the analyzed solutions, quality indices were introduced. The results of the simulation research indicate the influence of the track width of the wheels on the accuracy of motion when using the wheels’ controller, as well as its impact on energy efficiency. Moreover, they show that it is possible to significantly improve the accuracy of motion by using an additional pose controller, which allows limiting the impact of the non-optimal geometric parameters of the robot and the slip of the wheels on trajectory tracking errors. However, the addition of the pose controller does not significantly affect the energy efficiency during the robot’s motion, which may be even worse in this case. Full article
(This article belongs to the Section Robotics and Automation)
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24 pages, 8948 KiB  
Article
Adaptive Skid-Steering Control Approach for Robots on Uncertain Inclined Planes with Redundant Load-Bearing Mobility
by Lin Zhang, Baoyu Wang, Enguang Guan, Xun Liu, Muhammad Saqib and Yanzheng Zhao
Biomimetics 2024, 9(2), 64; https://doi.org/10.3390/biomimetics9020064 - 23 Jan 2024
Cited by 6 | Viewed by 2443
Abstract
Climbing manufacturing robots can create a revolutionary manufacturing paradigm for large and complex components, while the motion control of climbing manipulation-oriented robots (CMo-Rs) is still challenging considering anti-slippage problems. In this study, a CMo-R with full-scenery climbing capability and redundant load-bearing mobility is [...] Read more.
Climbing manufacturing robots can create a revolutionary manufacturing paradigm for large and complex components, while the motion control of climbing manipulation-oriented robots (CMo-Rs) is still challenging considering anti-slippage problems. In this study, a CMo-R with full-scenery climbing capability and redundant load-bearing mobility is designed based on magnetic adsorption. A four-wheel kinematic model considering the slipping phenomenon is established. An adaptive kinematic control algorithm based on slip estimation using Lyapunov theory is designed for uncertain inclined planes. For comparison, the traditional PID-based algorithm without slip consideration is implemented as well. Numeric simulations are conducted to tackle the trajectory tracking problems for both circular and linear trajectories on the horizontal plane (HP), 50° inclined plane (50° IP), 60° inclined plane (60° IP), and vertical plane (VP). The results prove that our approach achieves better tracking accuracy. It demonstrated applicability in various climbing scenarios with uncertain inclined planes. The results of experiments also validate the feasibility, applicability, and stability of the proposed approach. Full article
(This article belongs to the Special Issue Biomimetic Techniques for Optimization Problems in Engineering)
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