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Robotics
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Legged Robots into the Real World
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Legged Robots into the Real World

A special issue of Robotics (ISSN 2218-6581). This special issue belongs to the section "Humanoid and Human Robotics".

Deadline for manuscript submissions: closed (30 April 2023) | Viewed by 19322

Special Issue Editor

Dr. Chengxu Zhou

E-Mail Website
Guest Editor
School of Mechanical Engineering, University of Leeds, Leeds, UK
Interests: humanoid robotics; legged locomotion; motion planning; robot kinematics and dynamics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues, 

Legged robots are designed to extend human capabilities in various practice environments, especially in unstructured terrestrial applications. Quadruped robots, such as Boston Dynamics Spot, ANYbotics AYNmal, Unitree B1, etc., are unfolding promising prospects in several industries for sensing and inspection purposes. However, despite compelling achievements in recent years, legged robots, in general, are still far from being deployed in real world applications. There are still many challenges to be addressed.

This Special Issue focuses on the advancements in real world deployment of legged robots, from the novel mechanism, sensor and actuator design, to dynamic and robust motion generation using optimal control and machine learning approaches, aiming at unlocking the full potential of legged robots in practical scenarios.

Topics of interest include, but are not limited to:

  • The design and development of legged robots;
  • Advances in legged manipulators;
  • Dynamic legged locomotion;
  • Whole-body motion generation;
  • Reinforcement learning for legged robots;
  • Teleoperation of legged robots;
  • Jumping and running robots;
  • Sensing, perception and state estimation for legged robots;
  • Localization, mapping and navigation for legged robots;
  • Collaborative legged robots;
  • Real-world applications using legged robots.

Dr. Chengxu Zhou
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Robotics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • legged robots
  • legged locomotion
  • humanoids and animaloids, whole-body motion planning and control
  • machine learning for robot control
  • mobile manipulation
  • SLAM
  • telerobotics and teleoperation
  • physical human–robot interaction

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Related Special Issue

Published Papers (6 papers)

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Editorial

Jump to: Research

2 pages, 167 KiB  
Editorial
Special Issue “Legged Robots into the Real World”
by Chengxu Zhou
Robotics 2023, 12(4), 102; https://doi.org/10.3390/robotics12040102 - 13 Jul 2023
Viewed by 1434
Abstract
In the landscape of intelligent systems and robotics, legged robots stand out as a fascinating fusion of biological inspiration and engineered design [...] Full article
(This article belongs to the Special Issue Legged Robots into the Real World)

Research

Jump to: Editorial

13 pages, 10035 KiB  
Article
FastMimic: Model-Based Motion Imitation for Agile, Diverse and Generalizable Quadrupedal Locomotion
by Tianyu Li, Jungdam Won, Jeongwoo Cho, Sehoon Ha and Akshara Rai
Robotics 2023, 12(3), 90; https://doi.org/10.3390/robotics12030090 - 20 Jun 2023
Cited by 4 | Viewed by 2359
Abstract
Robots operating in human environments require a diverse set of skills, including slow and fast walking, turning, side-stepping, and more. However, developing robot controllers capable of exhibiting such a broad range of behaviors is a challenging problem that necessitates meticulous investigation for each [...] Read more.
Robots operating in human environments require a diverse set of skills, including slow and fast walking, turning, side-stepping, and more. However, developing robot controllers capable of exhibiting such a broad range of behaviors is a challenging problem that necessitates meticulous investigation for each task. To address this challenge, we introduce a trajectory optimization method that resolves the kinematic infeasibility of reference animal motions. This method, combined with a model-based controller, results in a unified data-driven model-based control framework capable of imitating various animal gaits without the need for expensive simulation training or real-world fine-tuning. Our framework is capable of imitating a variety of motor skills such as trotting, pacing, turning, and side-stepping with ease. It shows superior tracking capabilities in both simulations and the real world compared to other imitation controllers, including a model-based one and a learning-based motion imitation technique. Full article
(This article belongs to the Special Issue Legged Robots into the Real World)
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20 pages, 1798 KiB  
Article
Online Feet Potential Fields for Quadruped Robots Navigation in Harsh Terrains
by Viviana Morlando, Jonathan Cacace and Fabio Ruggiero
Robotics 2023, 12(3), 86; https://doi.org/10.3390/robotics12030086 - 13 Jun 2023
Cited by 3 | Viewed by 2900
Abstract
Quadruped robots have garnered significant attention in recent years due to their ability to navigate through challenging terrains. Among the various environments, agriculture fields are particularly difficult for legged robots, given the variability of soil types and conditions. To address this issue, this [...] Read more.
Quadruped robots have garnered significant attention in recent years due to their ability to navigate through challenging terrains. Among the various environments, agriculture fields are particularly difficult for legged robots, given the variability of soil types and conditions. To address this issue, this study proposes a novel navigation strategy that utilizes ground reaction forces to calculate online artificial potential fields, which are then applied to the robot’s feet to avoid low-traversability regions. The strategy also incorporates the net vector of the attractive potential field towards the goal and the repulsive field to avoid slippery regions, which dynamically adjusts the quadruped’s gait. A realistic simulation environment validates the proposed navigation framework with case studies on randomly generated terrains. A comprehensive comparison with baseline navigation methods is conducted to assess the effectiveness of the proposed approach. Full article
(This article belongs to the Special Issue Legged Robots into the Real World)
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18 pages, 3033 KiB  
Article
A Data-Driven Model Predictive Control for Quadruped Robot Steering on Slippery Surfaces
by Paolo Arena, Luca Patanè and Salvatore Taffara
Robotics 2023, 12(3), 67; https://doi.org/10.3390/robotics12030067 - 1 May 2023
Cited by 4 | Viewed by 3712
Abstract
In this paper, the locomotion and steering control of a simulated Mini Cheetah quadruped robot was investigated in the presence of terrain characterised by low friction. Low-level locomotion and steering control were implemented via a central pattern generator approach, whereas high-level steering control [...] Read more.
In this paper, the locomotion and steering control of a simulated Mini Cheetah quadruped robot was investigated in the presence of terrain characterised by low friction. Low-level locomotion and steering control were implemented via a central pattern generator approach, whereas high-level steering control manoeuvres were implemented by comparing a neural network and a linear model predictive controller in a dynamic simulation environment. A data-driven approach was adopted to identify the robot model using both a linear transfer function and a shallow artificial neural network. The results demonstrate that, whereas the linear approach showed good performance in high-friction terrain, in the presence of slippery conditions, the application of a neural network predictive controller improved trajectory accuracy and preserved robot safety with different steering manoeuvres. A comparative analysis was carried out using several performance indices. Full article
(This article belongs to the Special Issue Legged Robots into the Real World)
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18 pages, 4258 KiB  
Article
Optimization-Based Reference Generator for Nonlinear Model Predictive Control of Legged Robots
by Angelo Bratta, Michele Focchi, Niraj Rathod and Claudio Semini
Robotics 2023, 12(1), 6; https://doi.org/10.3390/robotics12010006 - 3 Jan 2023
Cited by 4 | Viewed by 3464
Abstract
Model predictive control (MPC) approaches are widely used in robotics, because they guarantee feasibility and allow the computation of updated trajectories while the robot is moving. They generally require heuristic references for the tracking terms and proper tuning of the parameters of the [...] Read more.
Model predictive control (MPC) approaches are widely used in robotics, because they guarantee feasibility and allow the computation of updated trajectories while the robot is moving. They generally require heuristic references for the tracking terms and proper tuning of the parameters of the cost function in order to obtain good performance. For instance, when a legged robot has to react to disturbances from the environment (e.g., to recover after a push) or track a specific goal with statically unstable gaits, the effectiveness of the algorithm can degrade. In this work, we propose a novel optimization-based reference generator which exploits a linear inverted pendulum (LIP) model to compute reference trajectories for the center of mass while taking into account the possible underactuation of a gait (e.g., in a trot). The obtained trajectories are used as references for the cost function of the nonlinear MPC presented in our previous work. We also present a formulation that ensures guarantees on the response time to reach a goal without the need to tune the weights of the cost terms. In addition, footholds are corrected by using the optimized reference to drive the robot toward the goal. We demonstrate the effectiveness of our approach both in simulations and experiments in different scenarios with the Aliengo robot. Full article
(This article belongs to the Special Issue Legged Robots into the Real World)
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24 pages, 6361 KiB  
Article
Benchmarking Dynamic Balancing Controllers for Humanoid Robots
by Juan A. Castano, Joseph Humphreys, Enrico Mingo Hoffman, Noelia Fernández Talavera, Maria Cristina Rodriguez Sanchez and Chengxu Zhou
Robotics 2022, 11(5), 114; https://doi.org/10.3390/robotics11050114 - 19 Oct 2022
Cited by 2 | Viewed by 3327
Abstract
This paper presents a comparison study of three control design approaches for humanoid balancing based on the Center of Mass (CoM) stabilization and body posture adjustment. The comparison was carried out under controlled circumstances allowing other researchers to replicate [...] Read more.
This paper presents a comparison study of three control design approaches for humanoid balancing based on the Center of Mass (CoM) stabilization and body posture adjustment. The comparison was carried out under controlled circumstances allowing other researchers to replicate and compare our results with their own. The feedback control from state space design is based on simple models and provides sufficient robustness to control complex and high Degrees of Freedom (DoFs) systems, such as humanoids. The implemented strategies allow compliant behavior of the robot in reaction to impulsive or periodical disturbances, resulting in a smooth and human-like response while considering constraints. In this respect, we implemented two balancing strategies to compensate for the CoM deviation. The first one uses the robot’s capture point as a stability principle and the second one uses the Force/Torque sensors at the ankles to define a CoM reference that stabilizes the robot. In addition, was implemented a third strategy based on upper body orientation to absorb external disturbances and counterbalance them. Even though the balancing strategies are implemented independently, they can be merged to further increase balancing performance. The proposed strategies were previously applied on different humanoid bipedal platforms, however, their performance could not be properly benchmarked before. With this concern, this paper focuses on benchmarking in controlled scenarios to help the community in comparing different balance techniques. The key performance indicators (KPIs) used in our comparison are the CoM deviation, the settling time, the maximum measured orientation, passive gait measure, measured ankles torques, and reconstructed Center of Pressure (CoP). The benchmarking experiments were carried out in simulations and using the facility at Istituto Italiano di Tecnologia on the REEM-C humanoid robot provided by PAL robotics inside the EU H2020 project EUROBENCH framework. Full article
(This article belongs to the Special Issue Legged Robots into the Real World)
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