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View article: Reinforcement Learning with Data Bootstrapping for Dynamic Subgoal Pursuit in Humanoid Robot Navigation
Reinforcement Learning with Data Bootstrapping for Dynamic Subgoal Pursuit in Humanoid Robot Navigation Open
Safe and real-time navigation is fundamental for humanoid robot applications. However, existing bipedal robot navigation frameworks often struggle to balance computational efficiency with the precision required for stable locomotion. We pr…
View article: Real-Time Safe Bipedal Robot Navigation using Linear Discrete Control Barrier Functions
Real-Time Safe Bipedal Robot Navigation using Linear Discrete Control Barrier Functions Open
Safe navigation in real-time is an essential task for humanoid robots in real-world deployment. Since humanoid robots are inherently underactuated thanks to unilateral ground contacts, a path is considered safe if it is obstacle-free and r…
View article: Time-Varying Foot-Placement Control for Underactuated Humanoid Walking on Swaying Rigid Surfaces
Time-Varying Foot-Placement Control for Underactuated Humanoid Walking on Swaying Rigid Surfaces Open
Locomotion on dynamic rigid surface (i.e., rigid surface accelerating in an inertial frame) presents complex challenges for controller design, which are essential for deploying humanoid robots in dynamic real-world environments such as mov…
View article: Moving past point-contacts: Extending the ALIP model to humanoids with non-trivial feet using hierarchical, full-body momentum control
Moving past point-contacts: Extending the ALIP model to humanoids with non-trivial feet using hierarchical, full-body momentum control Open
The Angular-Momentum Linear Inverted Pendulum (ALIP) model is a promising motion planner for bipedal robots. However, it relies on two assumptions: (1) the robot has point-contact feet or passive ankles, and (2) the angular momentum around…
View article: Unified Path and Gait Planning for Safe Bipedal Robot Navigation
Unified Path and Gait Planning for Safe Bipedal Robot Navigation Open
Safe path and gait planning are essential for bipedal robots to navigate complex real-world environments. The prevailing approaches often plan the path and gait separately in a hierarchical fashion, potentially resulting in unsafe movement…
View article: Adaptive Step Duration for Precise Foot Placement: Achieving Robust Bipedal Locomotion on Terrains with Restricted Footholds
Adaptive Step Duration for Precise Foot Placement: Achieving Robust Bipedal Locomotion on Terrains with Restricted Footholds Open
Traditional one-step preview planning algorithms for bipedal locomotion struggle to generate viable gaits when walking across terrains with restricted footholds, such as stepping stones. To overcome such limitations, this paper introduces …
View article: Safe Whole-Body Task Space Control for Humanoid Robots
Safe Whole-Body Task Space Control for Humanoid Robots Open
Complex robotic systems require whole-body controllers to deal with contact interactions, handle closed kinematic chains, and track task-space control objectives. However, for many applications, safety-critical controllers are important to…
View article: Template Model Inspired Task Space Learning for Robust Bipedal Locomotion
Template Model Inspired Task Space Learning for Robust Bipedal Locomotion Open
This work presents a hierarchical framework for bipedal locomotion that combines a Reinforcement Learning (RL)-based high-level (HL) planner policy for the online generation of task space commands with a model-based low-level (LL) controll…
View article: Data-Driven Latent Space Representation for Robust Bipedal Locomotion Learning
Data-Driven Latent Space Representation for Robust Bipedal Locomotion Learning Open
This paper presents a novel framework for learning robust bipedal walking by combining a data-driven state representation with a Reinforcement Learning (RL) based locomotion policy. The framework utilizes an autoencoder to learn a low-dime…
View article: Towards Standardized Disturbance Rejection Testing of Legged Robot Locomotion with Linear Impactor: A Preliminary Study, Observations, and Implications
Towards Standardized Disturbance Rejection Testing of Legged Robot Locomotion with Linear Impactor: A Preliminary Study, Observations, and Implications Open
Dynamic locomotion in legged robots is close to industrial collaboration, but a lack of standardized testing obstructs commercialization. The issues are not merely political, theoretical, or algorithmic but also physical, indicating limite…
View article: Time-Varying ALIP Model and Robust Foot-Placement Control for Underactuated Bipedal Robot Walking on a Swaying Rigid Surface
Time-Varying ALIP Model and Robust Foot-Placement Control for Underactuated Bipedal Robot Walking on a Swaying Rigid Surface Open
Controller design for bipedal walking on dynamic rigid surfaces (DRSes), which are rigid surfaces moving in the inertial frame (e.g., ships and airplanes), remains largely uninvestigated. This paper introduces a hierarchical control approa…
View article: Real-Time Navigation for Bipedal Robots in Dynamic Environments
Real-Time Navigation for Bipedal Robots in Dynamic Environments Open
The popularity of mobile robots has been steadily growing, with these robots being increasingly utilized to execute tasks previously completed by human workers. For bipedal robots to see this same success, robust autonomous navigation syst…
View article: Safe Path Planning for Polynomial Shape Obstacles via Control Barrier Functions and Logistic Regression
Safe Path Planning for Polynomial Shape Obstacles via Control Barrier Functions and Logistic Regression Open
Safe path planning is critical for bipedal robots to operate in safety-critical environments. Common path planning algorithms, such as RRT or RRT*, typically use geometric or kinematic collision check algorithms to ensure collision-free pa…
View article: On the Adversarial Scenario-based Safety Testing of Robots: the Comparability and Optimal Aggressiveness
On the Adversarial Scenario-based Safety Testing of Robots: the Comparability and Optimal Aggressiveness Open
This paper studies the class of scenario-based safety testing algorithms in the black-box safety testing configuration. For algorithms sharing the same state-action set coverage with different sampling distributions, it is commonly believe…
View article: Resolved Motion Control for 3D Underactuated Bipedal Walking using Linear Inverted Pendulum Dynamics and Neural Adaptation
Resolved Motion Control for 3D Underactuated Bipedal Walking using Linear Inverted Pendulum Dynamics and Neural Adaptation Open
We present a framework to generate periodic trajectory references for a 3D under-actuated bipedal robot, using a linear inverted pendulum (LIP) based controller with adaptive neural regulation. We use the LIP template model to estimate the…
View article: On Safety Testing, Validation, and Characterization with Scenario-Sampling: A Case Study of Legged Robots
On Safety Testing, Validation, and Characterization with Scenario-Sampling: A Case Study of Legged Robots Open
The dynamic response of the legged robot locomotion is non-Lipschitz and can be stochastic due to environmental uncertainties. To test, validate, and characterize the safety performance of legged robots, existing solutions on observed and …
View article: Reinforcement Learning-Based Cascade Motion Policy Design for Robust 3D Bipedal Locomotion
Reinforcement Learning-Based Cascade Motion Policy Design for Robust 3D Bipedal Locomotion Open
This paper presents a novel reinforcement learning (RL) framework to design cascade feedback control policies for 3D bipedal locomotion. Existing RL algorithms are often trained in an end-to-end manner or rely on prior knowledge of some re…
View article: Linear Policies are Sufficient to Realize Robust Bipedal Walking on Challenging Terrains
Linear Policies are Sufficient to Realize Robust Bipedal Walking on Challenging Terrains Open
In this work, we demonstrate robust walking in the bipedal robot Digit on uneven terrains by just learning a single linear policy. In particular, we propose a new control pipeline, wherein the high-level trajectory modulator shapes the end…
View article: Adaptive Feedback Regulator for Powered Lower-Limb Exoskeleton under Model Uncertainty
Adaptive Feedback Regulator for Powered Lower-Limb Exoskeleton under Model Uncertainty Open
This paper presents a neural network (NN) based adaptive feedback regulator to ensure the lateral and longitudinal stability and regulate the desired walking velocity of a lower-limb exoskeleton under model uncertainty. The traditional mod…
View article: Learning Linear Policies for Robust Bipedal Locomotion on Terrains with Varying Slopes
Learning Linear Policies for Robust Bipedal Locomotion on Terrains with Varying Slopes Open
In this paper, with a view toward deployment of light-weight control frameworks for bipedal walking robots, we realize end-foot trajectories that are shaped by a single linear feedback policy. We learn this policy via a model-free and a gr…
View article: Robust Feedback Motion Policy Design Using Reinforcement Learning on a 3D Digit Bipedal Robot
Robust Feedback Motion Policy Design Using Reinforcement Learning on a 3D Digit Bipedal Robot Open
In this paper, a hierarchical and robust framework for learning bipedal locomotion is presented and successfully implemented on the 3D biped robot Digit built by Agility Robotics. We propose a cascade-structure controller that combines the…
View article: Velocity Regulation of 3D Bipedal Walking Robots with Uncertain Dynamics Through Adaptive Neural Network Controller
Velocity Regulation of 3D Bipedal Walking Robots with Uncertain Dynamics Through Adaptive Neural Network Controller Open
This paper presents a neural-network based adaptive feedback control structure to regulate the velocity of 3D bipedal robots under dynamics uncertainties. Existing Hybrid Zero Dynamics (HZD)-based controllers regulate velocity through the …
View article: Hybrid Zero Dynamics Inspired Feedback Control Policy Design for 3D Bipedal Locomotion using Reinforcement Learning
Hybrid Zero Dynamics Inspired Feedback Control Policy Design for 3D Bipedal Locomotion using Reinforcement Learning Open
This paper presents a novel model-free reinforcement learning (RL) framework to design feedback control policies for 3D bipedal walking. Existing RL algorithms are often trained in an end-to-end manner or rely on prior knowledge of some re…
View article: Rapid Trajectory optimization Using C-FROST with Illustration on a Cassie-Series Dynamic Walking Biped
Rapid Trajectory optimization Using C-FROST with Illustration on a Cassie-Series Dynamic Walking Biped Open
One of the big attractions of low-dimensional models for gait design has been the ability to compute solutions rapidly, whereas one of their drawbacks has been the difficulty in mapping the solutions back to the target robot. This paper pr…
View article: Feedback Control of an Exoskeleton for Paraplegics: Toward Robustly Stable, Hands-Free Dynamic Walking
Feedback Control of an Exoskeleton for Paraplegics: Toward Robustly Stable, Hands-Free Dynamic Walking Open
This manuscript presents control of a high-DOF fully actuated lower-limb exoskeleton for paraplegic individuals. The key novelty is the ability for the user to walk without the use of crutches or other external means of stabilization. We h…
View article: Reinforcement Learning Meets Hybrid Zero Dynamics: A Case Study for RABBIT
Reinforcement Learning Meets Hybrid Zero Dynamics: A Case Study for RABBIT Open
The design of feedback controllers for bipedal robots is challenging due to the hybrid nature of its dynamics and the complexity imposed by high-dimensional bipedal models. In this paper, we present a novel approach for the design of feedb…
View article: Feedback Control of a Cassie Bipedal Robot: Walking, Standing, and Riding a Segway
Feedback Control of a Cassie Bipedal Robot: Walking, Standing, and Riding a Segway Open
The Cassie bipedal robot designed by Agility Robotics is providing academics a common platform for sharing and comparing algorithms for locomotion, perception, and navigation. This paper focuses on feedback control for standing and walking…
View article: Rapid Trajectory Optimization Using C-FROST with Illustration on a\n Cassie-Series Dynamic Walking Biped
Rapid Trajectory Optimization Using C-FROST with Illustration on a\n Cassie-Series Dynamic Walking Biped Open
One of the big attractions of low-dimensional models for gait design has been\nthe ability to compute solutions rapidly, whereas one of their drawbacks has\nbeen the difficulty in mapping the solutions back to the target robot. This\npaper…
View article: Rapid Bipedal Gait Design Using C-FROST with Illustration on a Cassie-series Robot.
Rapid Bipedal Gait Design Using C-FROST with Illustration on a Cassie-series Robot. Open
One of the big attractions of low-dimensional models for gait design has been the ability to compute solutions rapidly, whereas one of their drawbacks has been the difficulty in mapping the solutions back to the target robot. This paper pr…