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Keywords = wheeled–legged

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25 pages, 6969 KiB  
Article
An Analysis of the Design and Kinematic Characteristics of an Octopedic Land–Air Bionic Robot
by Jianwei Zhao, Jiaping Gao, Mingsong Bao, Hao Zhai, Xu Pei and Zheng Jiang
Sensors 2025, 25(14), 4502; https://doi.org/10.3390/s25144502 - 19 Jul 2025
Viewed by 341
Abstract
The urgent need for complex terrain adaptability in industrial automation and disaster relief has highlighted the great potential of octopedal wheel-legged robots. However, their design complexity and motion control challenges must be addressed. In this study, an innovative design approach is employed to [...] Read more.
The urgent need for complex terrain adaptability in industrial automation and disaster relief has highlighted the great potential of octopedal wheel-legged robots. However, their design complexity and motion control challenges must be addressed. In this study, an innovative design approach is employed to construct a highly adaptive robot architecture capable of intelligently adjusting the wheel-leg configuration to cope with changing environments. An advanced kinematic analysis and simulation techniques are combined with inverse kinematic algorithms and dynamic planning to achieve a typical ‘Step-Wise Octopedal Dynamic Coordination Gait’ and different gait planning and optimization. The effectiveness of the design and control strategy is verified through the construction of an experimental platform and field tests, significantly improving the robot’s adaptability and mobility in complex terrain. Additionally, an optional integrated quadrotor module with a compact folding mechanism is incorporated, enabling the robot to overcome otherwise impassable obstacles via short-distance flight when ground locomotion is impaired. This achievement not only enriches the theory and methodology of the multi-legged robot design but also establishes a solid foundation for its widespread application in disaster rescue, exploration, and industrial automation. Full article
(This article belongs to the Section Sensors and Robotics)
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21 pages, 9720 KiB  
Article
Rolling vs. Swing: A Strategy for Enhancing Locomotion Speed and Stability in Legged Robots
by Yongjiang Xue, Wei Wang, Mingyu Duan, Nanqing Jiang, Shaoshi Zhang and Xuan Xiao
Biomimetics 2025, 10(7), 435; https://doi.org/10.3390/biomimetics10070435 - 2 Jul 2025
Viewed by 407
Abstract
Legged robots face inherent challenges in energy efficiency and stability at high speeds due to the repetitive acceleration–deceleration cycles of swing-based locomotion. To address these limitations, this paper presents a motion strategy that uses rolling gait instead of swing gait to improve the [...] Read more.
Legged robots face inherent challenges in energy efficiency and stability at high speeds due to the repetitive acceleration–deceleration cycles of swing-based locomotion. To address these limitations, this paper presents a motion strategy that uses rolling gait instead of swing gait to improve the energy efficiency and stability. First, a wheel-legged quadruped robot, R-Taichi, is developed, which is capable of switching to legged, wheeled, and RHex mobile modes. Second, the mechanical structure of the transformable two-degree-of-freedom leg is introduced, and the kinematics is analyzed. Finally, experiments are conducted to generate wheeled, legged, and RHex motion in both swing and rolling gaits, and the energy efficiency is further compared. The experimental results show that the rolling motion can ensure stable ground contact and mitigate cyclic collisions, reducing specific resistance by up to 30% compared with conventional swing gaits, achieving a top speed of 0.7 m/s with enhanced stability (root mean square error (RMSE) reduction of 22% over RHex mode). Furthermore, R-Taichi exhibits robust multi-terrain adaptability, successfully traversing gravel, grass, and obstacles up to 150 mm in height. Full article
(This article belongs to the Special Issue Biomimetic Robot Motion Control)
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22 pages, 5516 KiB  
Article
Technology and Method Optimization for Foot–Ground Contact Force Detection in Wheel-Legged Robots
by Chao Huang, Meng Hong, Yaodong Wang, Hui Chai, Zhuo Hu, Zheng Xiao, Sijia Guan and Min Guo
Sensors 2025, 25(13), 4026; https://doi.org/10.3390/s25134026 - 27 Jun 2025
Viewed by 346
Abstract
Wheel-legged robots combine the advantages of both wheeled robots and traditional quadruped robots, enhancing terrain adaptability but posing higher demands on the perception of foot–ground contact forces. However, existing approaches still suffer from limited accuracy in estimating contact positions and three-dimensional contact forces [...] Read more.
Wheel-legged robots combine the advantages of both wheeled robots and traditional quadruped robots, enhancing terrain adaptability but posing higher demands on the perception of foot–ground contact forces. However, existing approaches still suffer from limited accuracy in estimating contact positions and three-dimensional contact forces when dealing with flexible tire–ground interactions. To address this challenge, this study proposes a foot–ground contact state detection technique and optimization method based on multi-sensor fusion and intelligent modeling for wheel-legged robots. First, finite element analysis (FEA) is used to simulate strain distribution under various contact conditions. Combined with global sensitivity analysis (GSA), the optimal placement of PVDF sensors is determined and experimentally validated. Subsequently, under dynamic gait conditions, data collected from the PVDF sensor array are used to predict three-dimensional contact forces through Gaussian process regression (GPR) and artificial neural network (ANN) models. A custom experimental platform is developed to replicate variable gait frequencies and collect dynamic contact data for validation. The results demonstrate that both GPR and ANN models achieve high accuracy in predicting dynamic 3D contact forces, with normalized root mean square error (NRMSE) as low as 8.04%. The models exhibit reliable repeatability and generalization to novel inputs, providing robust technical support for stable contact perception and motion decision-making in complex environments. Full article
(This article belongs to the Section Sensors and Robotics)
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21 pages, 5263 KiB  
Article
Design and Analysis of an Adaptable Wheeled-Legged Robot for Vertical Locomotion
by Ernesto Christian Orozco-Magdaleno, Eduardo Castillo-Castañeda, Omar Rodríguez-Abreo and Giuseppe Carbone
Robotics 2025, 14(6), 79; https://doi.org/10.3390/robotics14060079 - 10 Jun 2025
Viewed by 662
Abstract
Most of the developed and studied service robots for vertical locomotion, as visual inspection, are made up by a rigid body with legs, wheels, or both. Thus, the robot can only displace over regular and/or flat surfaces since it is not able to [...] Read more.
Most of the developed and studied service robots for vertical locomotion, as visual inspection, are made up by a rigid body with legs, wheels, or both. Thus, the robot can only displace over regular and/or flat surfaces since it is not able to adapt to the irregularities and projections of the wall. Therefore, this paper presents the design and analysis of an adaptable robot for vertical locomotion service tasks, which has a body made up of four wheeled legs that can easily adapt to the different irregularities and projections of building facades. The robot uses an Electric Ducted Fan (EDF) as the vortex adhesion system. Each leg has a rubber cover, which allows a higher mechanical adaptability of the robot over different irregularities of the wall. Theoretical backgrounds and open issues are addressed by considering some challenging problems such as mechanical adaptability modeling as well as kinematic and static analysis. Laser sensors are mounted over the robot to measure the adaptability of the robot, between the legs and body, at each time of the experimental tests for vertical locomotion. Full article
(This article belongs to the Special Issue Legged Robots into the Real World, 2nd Edition)
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33 pages, 12896 KiB  
Article
A Bipedal Robotic Platform Leveraging Reconfigurable Locomotion Policies for Terrestrial, Aquatic, and Aerial Mobility
by Zijie Sun, Yangmin Li and Long Teng
Biomimetics 2025, 10(6), 374; https://doi.org/10.3390/biomimetics10060374 - 5 Jun 2025
Viewed by 758
Abstract
Biological systems can adaptively navigate multi-terrain environments via morphological and behavioral flexibility. While robotic systems increasingly achieve locomotion versatility in one or two domains, integrating terrestrial, aquatic, and aerial mobility into a single platform remains an engineering challenge. This work tackles this by [...] Read more.
Biological systems can adaptively navigate multi-terrain environments via morphological and behavioral flexibility. While robotic systems increasingly achieve locomotion versatility in one or two domains, integrating terrestrial, aquatic, and aerial mobility into a single platform remains an engineering challenge. This work tackles this by introducing a bipedal robot equipped with a reconfigurable locomotion framework, enabling seven adaptive policies: (1) thrust-assisted jumping, (2) legged crawling, (3) balanced wheeling, (4) tricycle wheeling, (5) paddling-based swimming, (6) air-propelled drifting, and (7) quadcopter flight. Field experiments and indoor statistical tests validated these capabilities. The robot achieved a 3.7-m vertical jump via thrust forces counteracting gravitational forces. A unified paddling mechanism enabled seamless transitions between crawling and swimming modes, allowing amphibious mobility in transitional environments such as riverbanks. The crawling mode demonstrated the traversal on uneven substrates (e.g., medium-density grassland, soft sand, and cobblestones) while generating sufficient push forces for object transport. In contrast, wheeling modes prioritize speed and efficiency on flat terrain. The aquatic locomotion was validated through trials in static water, an open river, and a narrow stream. The flight mode was investigated with the assistance of the jumping mechanism. By bridging terrestrial, aquatic, and aerial locomotion, this platform may have the potential for search-and-rescue and environmental monitoring applications. Full article
(This article belongs to the Section Locomotion and Bioinspired Robotics)
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37 pages, 14623 KiB  
Review
Research Review of Agricultural Machinery Power Chassis in Hilly and Mountainous Areas
by Yiyong Jiang, Ruochen Wang, Renkai Ding, Zeyu Sun, Yu Jiang and Wei Liu
Agriculture 2025, 15(11), 1158; https://doi.org/10.3390/agriculture15111158 - 28 May 2025
Viewed by 748
Abstract
The terrain in hilly and mountainous areas is complex, and the level of agricultural mechanization is low. This article systematically reviews the research progress of key technologies for agricultural machinery power chassis in hilly and mountainous areas, and conducts an analysis of five [...] Read more.
The terrain in hilly and mountainous areas is complex, and the level of agricultural mechanization is low. This article systematically reviews the research progress of key technologies for agricultural machinery power chassis in hilly and mountainous areas, and conducts an analysis of five aspects: the power system, walking system, steering system, leveling system, and automatic navigation and path tracking control system. In this manuscript, (1) in terms of the power system, the technical characteristics and application scenarios of mechanical, hydraulic, and electric drive systems were compared. (2) In terms of the walking system, the performance differences between wheeled, crawler, legged, and composite walking devices and the application of suspension systems in agricultural machinery chassis were discussed. (3) In terms of the steering system, the steering characteristics of wheeled chassis and crawler chassis were analyzed, respectively. (4) In terms of the leveling system, the research progress on hydraulic and electric leveling mechanisms, as well as intelligent leveling control algorithms, was summarized. (5) The technology of automatic navigation and path tracking for agricultural machinery chassis was discussed, focusing on multi-sensor fusion and advanced control algorithms. In the future, agricultural machinery chassis will develop towards the directions of intelligence, automation, greening, being lightweight, and being multi-functionality. Full article
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20 pages, 6861 KiB  
Article
A Stair-Climbing Wheelchair with Novel Spoke Wheels for Smooth Motion
by Yuting Li, Zhong Wei, Jinlin Guo, Jinyao Ren, Yu Ding, Weixi Wang, Jia Liu and Aiguo Song
Appl. Sci. 2025, 15(10), 5433; https://doi.org/10.3390/app15105433 - 13 May 2025
Viewed by 455
Abstract
With the aging population and rising demand for assistive devices, electric wheelchairs have garnered significant attention. However, existing stair-climbing wheelchairs often suffer from complex structural complexity and limited flexibility. Spoke-wheel mechanisms, known for their simple structure and strong obstacle-crossing capabilities, hold promise but [...] Read more.
With the aging population and rising demand for assistive devices, electric wheelchairs have garnered significant attention. However, existing stair-climbing wheelchairs often suffer from complex structural complexity and limited flexibility. Spoke-wheel mechanisms, known for their simple structure and strong obstacle-crossing capabilities, hold promise but experience oscillation on flat terrain. This paper proposes an improved spoke-wheel mechanism (Flexwheel), which integrates springs into the spokes. These springs compress to varying lengths under gravitational force during ground contact, while sliding grooves and pre-compression constraints regulate spoke length, ensuring a stable height. A novel selection method for the optimal spring constant is developed based on mass, spoke length, and the number of spokes. This mathematical framework is applicable to stable, smooth ground motion under varying friction conditions between the upper and lower spokes. A wheelchair prototype equipped with four Flexwheels, a self-balancing mechanism, and multi-sensor fusion technology is designed. The simulation results indicate that Flexwheel reduces the range in body height from 10.75 mm (traditional spoke wheels) to 3.39 mm on flat terrain, a 68.47% improvement. During stair climbing, Flexwheel significantly reduces body oscillation compared to traditional spoke or circular wheels. Physical experiments validate that Flexwheel exhibits a 6.28 mm height fluctuation vs. traditional spokes wheels’ 12.13 mm, a 48.28% improvement, demonstrating its effectiveness in enhancing wheelchair stability and adaptability. Full article
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22 pages, 6354 KiB  
Article
A Novel Integrated Path Planning and Mode Decision Algorithm for Wheel–Leg Vehicles in Unstructured Environment
by Kui Wang, Xitao Wu, Shaoyang Shi, Mingfan Xu, Yifei Han, Zhewei Zhu and Yechen Qin
Sensors 2025, 25(9), 2888; https://doi.org/10.3390/s25092888 - 3 May 2025
Viewed by 579
Abstract
Human exploration and rescue in unstructured environments including hill terrain and depression terrain are fraught with danger and difficulty, making autonomous vehicles a promising alternative in these areas. In flat terrain, traditional wheeled vehicles demonstrate excellent maneuverability; however, their passability is limited in [...] Read more.
Human exploration and rescue in unstructured environments including hill terrain and depression terrain are fraught with danger and difficulty, making autonomous vehicles a promising alternative in these areas. In flat terrain, traditional wheeled vehicles demonstrate excellent maneuverability; however, their passability is limited in unstructured terrains due to the constraints of the chassis and drivetrain. Considering the high passability and exploration efficiency, wheel–leg vehicles have garnered increasing attention in recent years. In the automation process of wheel–leg vehicles, planning and mode decisions are crucial components. However, current path planning and mode decision algorithms are mostly designed for wheeled vehicles and cannot determine when to adopt which mode, thus limiting the full exploitation of the multimodal advantages of wheel–leg vehicles. To address this issue, this paper proposes an integrated path planning and mode decision algorithm (IPP-MD) for wheel–leg vehicles in unstructured environments, modeling the mode decision problem using a Markov Decision Process (MDP). The state space, action space, and reward function are innovatively designed to dynamically determine the most suitable mode of progression, fully utilizing the potential of wheel–leg vehicles in autonomous movement. The simulation results show that the proposed method demonstrates significant advantages in terms of fewer mode-switching occurrences compared to existing methods. Full article
(This article belongs to the Section Vehicular Sensing)
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9 pages, 2950 KiB  
Proceeding Paper
Cost-Effective Triboelectric-Assisted Sensory Actuator Designed for Intelligent Robot and Exoskeleton
by Haowen Liu, Yusong Chu, Yudong Zhao, Guanyu Zhu, Xuan Li, Minglu Zhu and Tao Chen
Eng. Proc. 2024, 78(1), 11; https://doi.org/10.3390/engproc2024078011 - 18 Apr 2025
Viewed by 2427
Abstract
Joint actuators are the key components in the innovation and iterative optimization of the robots, with a significant impact on both the performances of robots and manufacturing costs. Conventional industrial collaborative robots often use high-precision position and torque sensors, which are not cost-effective [...] Read more.
Joint actuators are the key components in the innovation and iterative optimization of the robots, with a significant impact on both the performances of robots and manufacturing costs. Conventional industrial collaborative robots often use high-precision position and torque sensors, which are not cost-effective or energy-efficient in specific applications like assistive exoskeletons, legged robots, or wheeled robots. Alternatively, we propose a triboelectric-assisted sensory actuator that balances lightweight design, performance, and affordability for large-scale applications. The actuator is composed of a high-power density motor, a low reduction gearbox, and integrated with a rotational triboelectric sensor, which leads to high dynamic performances and low power consumption. The feasibility of the prototype is initially verified by characterizing the angular positioning accuracy and the back drivability. Experiments indicate that the rotational triboelectric sensor is able to accurately detect the angular displacement of the actuator with the self-generated signals. Overall, a highly integrated actuator module with the actuation and sensing circuit is fabricated as a compact design ready for assembling a complete intelligent robot. This actuator holds great potential as a cost-effective, energy-efficient, and versatile solution for modern robotics, crucial for advancing this field and improving human convenience. Full article
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19 pages, 7825 KiB  
Article
Jump Control Based on Nonlinear Wheel-Spring-Loaded Inverted Pendulum Model: Validation of a Wheeled-Bipedal Robot with Single-Degree-of-Freedom Legs
by Jingsong Gao, Hongzhe Jin, Liang Gao, Yanhe Zhu, Jie Zhao and Hegao Cai
Biomimetics 2025, 10(4), 246; https://doi.org/10.3390/biomimetics10040246 - 17 Apr 2025
Cited by 1 | Viewed by 548
Abstract
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 [...] Read more.
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
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21 pages, 1066 KiB  
Article
Enhancing Quadruped Robot Walking on Unstructured Terrains: A Combination of Stable Blind Gait and Deep Reinforcement Learning
by Shirelle Drori Marcus, Amir Shapiro and Chen Giladi
Electronics 2025, 14(7), 1431; https://doi.org/10.3390/electronics14071431 - 2 Apr 2025
Cited by 1 | Viewed by 1605
Abstract
Legged robots, designed for high adaptability, are poised for deployment in hazardous tasks traditionally undertaken by humans, particularly in unstructured terrains where their wheeled counterparts cannot operate. Nevertheless, using them in unstructured settings necessitates advanced control techniques to maneuver without depending entirely on [...] Read more.
Legged robots, designed for high adaptability, are poised for deployment in hazardous tasks traditionally undertaken by humans, particularly in unstructured terrains where their wheeled counterparts cannot operate. Nevertheless, using them in unstructured settings necessitates advanced control techniques to maneuver without depending entirely on visual signals or pre-programmed instructions. To address these challenges, this research proposes a novel walking algorithm for quadruped robots that blends a stable blind gait without needing any visual cues with deep reinforcement learning to enhance mobility across diverse terrains. The algorithm’s effectiveness was evaluated virtually, emphasizing the ability to regulate the robot’s leg movements and posture when reaching obstacles. Our results demonstrated a success rate of over 90% in the stair-climbing task, suggesting that the algorithm improved the robot’s mobility and stability. Although emphasizing a steady blind gait reduces reliance on visual cues, incorporating the algorithm with further sensory inputs and environmental awareness may improve the robot’s functionality and versatility in practical situations. More dynamic gaits and a wider variety of static and dynamic obstacles will be the focus of future algorithm development. Furthermore, validation in the real world will aid in detecting any shortcomings or potential areas for enhancement in the algorithm, thereby improving its adaptability and resilience in diverse settings and assignments. Full article
(This article belongs to the Special Issue Robotics: From Technologies to Applications)
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14 pages, 8704 KiB  
Article
Development of a Four Omni-Wheeled Mobile Robot Using Telescopic Legs
by Shuaiby Mohamed, Venkatesan Vellaiyan, Kangmin Kim, Youngshik Kim and Buhyun Shin
Machines 2025, 13(4), 292; https://doi.org/10.3390/machines13040292 - 31 Mar 2025
Cited by 1 | Viewed by 830
Abstract
This paper presents the design of a four omni-wheeled mobile robot consisting of four omni wheels, with each wheel connecting to a separate DC motor. Additionally, the presence of a telescopic leg with a linear RC servo actuator enables the robot to adapt [...] Read more.
This paper presents the design of a four omni-wheeled mobile robot consisting of four omni wheels, with each wheel connecting to a separate DC motor. Additionally, the presence of a telescopic leg with a linear RC servo actuator enables the robot to adapt to various landscape changes, including obstacle overcoming. We have designed and manufactured the physical prototype of the robot based on the simulation results. The proposed robot can traverse in both vertical and horizontal directions without altering its orientation, thereby enhancing its stability during operation. The experimental results confirm the robot’s effectiveness in autonomously adapting its position in response to sudden changes in the landscape, enabling it to navigate and climb steps successfully. Full article
(This article belongs to the Section Automation and Control Systems)
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23 pages, 10476 KiB  
Article
Balance Control Method for Bipedal Wheel-Legged Robots Based on Friction Feedforward Linear Quadratic Regulator
by Aimin Zhang, Renyi Zhou, Tie Zhang, Jingfu Zheng and Shouyan Chen
Sensors 2025, 25(4), 1056; https://doi.org/10.3390/s25041056 - 10 Feb 2025
Cited by 1 | Viewed by 1337
Abstract
With advancements in mobile robot technology, wheel-legged robots have emerged as promising next-generation mobile solutions, reducing design costs and enhancing adaptability in unstructured environments. As underactuated systems, their balance control has become a prominent research focus. Despite there being numerous control approaches, challenges [...] Read more.
With advancements in mobile robot technology, wheel-legged robots have emerged as promising next-generation mobile solutions, reducing design costs and enhancing adaptability in unstructured environments. As underactuated systems, their balance control has become a prominent research focus. Despite there being numerous control approaches, challenges remain. Balance control methods for wheel-legged robots are influenced by hardware characteristics, such as motor friction, which can induce oscillations and hinder dynamic convergence. This paper presents a friction feedforward Linear Quadratic Regulator (LQR) balance control method. Specifically, a basic LQR controller is developed based on the dynamics model of the wheel-legged robot, and a Stribeck friction model is established to characterize motor friction. A constant-speed excitation trajectory is designed to gather data for friction identification, and the Particle Swarm Optimization (PSO) algorithm is applied to determine the optimal friction parameters. The identified friction model is subsequently incorporated as feedforward compensation for the LQR controller’s torque output, resulting in the proposed friction feedforward LQR balance control algorithm. The minimum standard deviation for friction identification is approximately 0.30, and the computed friction model values closely match the actual values, indicating effective and accurate identification results. Balance experiments demonstrate that under diverse conditions—such as flat ground, single-sided bridges, and disturbance scenarios—the convergence performance of the friction feedforward LQR algorithm markedly surpasses that of the baseline LQR, effectively reducing oscillations, accelerating convergence, and improving the robot’s stability and robustness. Full article
(This article belongs to the Section Sensors and Robotics)
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20 pages, 21190 KiB  
Article
Whole-Body Control with Uneven Terrain Adaptability Strategy for Wheeled-Bipedal Robots
by Biao Wang, Yaxian Xin, Chao Chen, Zihao Song, Baoshuai Sun and Tianshuai Guo
Electronics 2025, 14(1), 198; https://doi.org/10.3390/electronics14010198 - 5 Jan 2025
Viewed by 1573
Abstract
Wheeled-bipedal robots (WBRs) integrate the locomotion efficiency and terrain adaptability of legged and wheeled robots. However, terrain adaptability is significantly influenced by the control system. This paper proposes a hierarchical control method for WBRs that includes an active force solver, a whole-body pose [...] Read more.
Wheeled-bipedal robots (WBRs) integrate the locomotion efficiency and terrain adaptability of legged and wheeled robots. However, terrain adaptability is significantly influenced by the control system. This paper proposes a hierarchical control method for WBRs that includes an active force solver, a whole-body pose planner and a whole-body torque controller. The active force solver based on model predictive control (MPC) was constructed to calculate the active force from the wheeled legs to the torso to achieve the torso’s desired motion tasks. The whole-body pose planner based on the terrain adaptability strategy provides whole-body joint trajectories that can achieve dynamic balance and movement simultaneously without external sensing information. The whole-body torque controller is used to calculate whole-body joint torque based on the active force reference and joint motion reference. Finally, two simulation experiments were conducted to verify the effectiveness of the proposed method on uneven terrain. Full article
(This article belongs to the Special Issue Advancements in Robotics: Perception, Manipulation, and Interaction)
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23 pages, 10631 KiB  
Article
Multi-Agent Reinforcement Learning Tracking Control of a Bionic Wheel-Legged Quadruped
by Rezwan Al Islam Khan, Chenyun Zhang, Zhongxiao Deng, Anzheng Zhang, Yuzhen Pan, Xuan Zhao, Huiliang Shang and Ruijiao Li
Machines 2024, 12(12), 902; https://doi.org/10.3390/machines12120902 - 9 Dec 2024
Cited by 1 | Viewed by 2715
Abstract
This paper presents a novel approach to developing control strategies for mobile robots, specifically the Pegasus, a bionic wheel-legged quadruped robot with unique chassis mechanics that enable four-wheel independent steering and diverse gaits. A multi-agent (MA) reinforcement learning (RL) controller is proposed, treating [...] Read more.
This paper presents a novel approach to developing control strategies for mobile robots, specifically the Pegasus, a bionic wheel-legged quadruped robot with unique chassis mechanics that enable four-wheel independent steering and diverse gaits. A multi-agent (MA) reinforcement learning (RL) controller is proposed, treating each leg as an independent agent with the goal of autonomous learning. The framework involves a multi-agent setup to model torso and leg dynamics, incorporating motion guidance optimization signal in the policy training and reward function. By doing so, we address leg schedule patterns for the complex configuration of the Pegasus, the requirement for various gaits, and the design of reward functions for MA-RL agents. Agents were trained using two variations of policy networks based on the framework, and real-world tests show promising results with easy policy transfer from simulation to the actual hardware. The proposed framework models acquired higher rewards and converged faster in training than other variants. Various experiments on the robot deployed framework showed fast response (0.8 s) under disturbance and low linear, angular velocity, and heading error, which was 2.5 cm/s, 0.06 rad/s, and 4°, respectively. Overall, the study demonstrates the feasibility of the proposed MA-RL control framework. Full article
(This article belongs to the Special Issue Design and Application of Bionic Robots)
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