A Survey of Wheeled-Legged Robots

Bjelonic, Marko; Klemm, Victor; Hutter, Marco

doi:10.1007/978-3-031-15226-9_11

Cited by 10 publications

(2 citation statements)

References 53 publications

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“…In general, robots can be classified into two main categories: wheeled robots and legged robots [1]. Furthermore, it's possible to combine wheeled and legged components to create various types of robots [2]. While wheeled robots are common, legged robots mimic nature and offer superior efficiency.…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Reinforcement Learning Algorithms for Bipedal Robot Locomotion

Aydogmus,

Yilmaz

2024

IEEE Access

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In this research, an optimization methodology was introduced for improving bipedal robot locomotion controlled by reinforcement learning (RL) algorithms. Specifically, the study focused on optimizing the Proximal Policy Optimization (PPO), Advantage Actor-Critic (A2C), Soft Actor-Critic (SAC), and Twin Delayed Deep Deterministic Policy Gradients (TD3) algorithms. The optimization process utilized the Tree-structured Parzen Estimator (TPE), a Bayesian optimization technique. All RL algorithms were applied to the same environment, which was created within the OpenAI GYM framework and known as the bipedal walker. The optimization involved the fine-tuning of key hyperparameters, including learning rate, discount factor, generalized advantage estimation, entropy coefficient, and Polyak update parameters. The study comprehensively analyzed the impact of these hyperparameters on the performance of RL algorithms. The results of the optimization efforts were promising, as the fine-tuned RL algorithms demonstrated significant improvements in performance. The mean reward values for the 10 trials were as follows: PPO achieved an average reward of 181.3, A2C obtained an average reward of −122.2, SAC reached an average reward of 320.3, and TD3 had an average reward of 278.6. These outcomes underscore the effectiveness of the optimization approach in enhancing the locomotion capabilities of the bipedal robot using RL techniques.

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Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Reinforcement Learning Algorithms for Bipedal Robot Locomotion

Aydogmus,

Yilmaz

2024

IEEE Access

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“…Tian et al [20] present a motion planning method for six-legged robot using optimized the configuration approach. Researchers from ETH [21,22] use an online trajectory optimization framework based on the ZMP approach for wheeled-legged quadrupedal robots. The hierarchical control framework optimizes whole-body accelerations and contact forces to improve the robustness of the robot.…”

Section: Introductionmentioning

confidence: 99%

Kinematic modeling and hybrid motion planning for wheeled-legged rovers to traverse challenging terrains

Zhu,

He,

Sun

2023

Robotica

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This paper presents a kinematics modeling and hybrid motion planning framework for wheeled-legged rovers. It is a unified solution for wheeled-legged rovers to traverse multiple challenging terrains using hybrid locomotion. A kinematic model is first established to describe the rover’s motions. Then, a hybrid motion planning framework is proposed to determine the rover’s gait patterns and parameterize the legs’ and the body’s trajectories. Furthermore, an optimization algorithm based on B-spline is utilized to minimize the motors’ energy dissipation and generate smooth trajectories. The wheeled and legged hybridization allows the rover for faster locomotion while maintaining high stability. Besides, it also improves the rover’s ability to overcome obstacles. Prototype experiments are carried out in more complex environments to verify the rover’s flexibility and maneuverability to traverse irregular terrains. The proposed algorithm reduces the swing amplitude by 83.3% compared to purely legged locomotion.

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Design Optimization of a Four-Bar Leg Linkage for a Legged-Wheeled Balancing Robot

Klemm

Mannhart

Siegwart

2022

Lecture Notes in Networks and Systems

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A Survey of Wheeled-Legged Robots

Cited by 10 publications

References 53 publications

Comparative Analysis of Reinforcement Learning Algorithms for Bipedal Robot Locomotion

Comparative Analysis of Reinforcement Learning Algorithms for Bipedal Robot Locomotion

Kinematic modeling and hybrid motion planning for wheeled-legged rovers to traverse challenging terrains

Design Optimization of a Four-Bar Leg Linkage for a Legged-Wheeled Balancing Robot

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