Luis Sentis

Luis Sentis
University of Texas at Austin | UT · Department of Aerospace Engineering & Engineering Mechanics

Doctor of Philosophy

About

188
Publications
45,967
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3,817
Citations
Citations since 2016
125 Research Items
2487 Citations
20162017201820192020202120220100200300400
20162017201820192020202120220100200300400
20162017201820192020202120220100200300400
20162017201820192020202120220100200300400

Publications

Publications (188)
Preprint
Model generalization of the underlying dynamics is critical for achieving data efficiency when learning for robot control. This paper proposes a novel approach for learning dynamics leveraging the symmetry in the underlying robotic system, which allows for robust extrapolation from fewer samples. Existing frameworks that represent all data in vecto...
Preprint
Full-text available
In this paper, we introduce the humanoid robot DRACO 3 by providing a high-level description of its design and control. This robot features proximal actuation and mechanical artifacts to provide a high range of hip, knee and ankle motion. Its versatile design brings interesting problems as it requires a more elaborate control system to perform its...
Article
We present a comprehensive formulation to the problem of controlling a high-dimensional robotic system involving complex tasks subject to a variety of constraints, obstacles, balance, and contact challenges. Using intuitive and natural representations, the approach is initiated by establishing individual objectives for a task and its constraints. S...
Preprint
This paper proposes a real-time model predictive control (MPC) scheme to execute multiple tasks using robots over a finite-time horizon. In industrial robotic applications, we must carefully consider multiple constraints for avoiding joint position, velocity, and torque limits. In addition, singularity-free and smooth motions require executing task...
Preprint
We tackle the problem of perceptive locomotion in dynamic environments. In this problem, a quadrupedal robot must exhibit robust and agile walking behaviors in response to environmental clutter and moving obstacles. We present a hierarchical learning framework, named PRELUDE, which decomposes the problem of perceptive locomotion into high-level dec...
Article
Full-text available
Firm foot contact is the top priority of climbing robots to avoid catastrophic events, especially when working at height. This study proposes a robust planning and control framework for climbing robots that provides robustness to slippage in unknown environments. The framework includes 1) a center of mass (CoM) trajectory optimization under the est...
Article
Full-text available
This paper proposes CONCERTS: Coverage competency-based target search, a failure-resilient path-planning algorithm for heterogeneous robot teams performing target searches for static targets in indoor and outdoor environments. This work aims to improve search completion time for realistic scenarios such as search and rescue or surveillance, while m...
Article
Full-text available
Contact-based decision and planning methods are becoming increasingly important to endow higher levels of autonomy for legged robots. Formal synthesis methods derived from symbolic systems have great potential for reasoning about high-level locomotion decisions and achieving complex maneuvering behaviors with correctness guarantees. This study take...
Preprint
Full-text available
This paper proposes KC-TSS: K-Clustered-Traveling Salesman Based Search, a failure resilient path planning algorithm for heterogeneous robot teams performing target search in human environments. We separate the sample path generation problem into Heterogeneous Clustering and multiple Traveling Salesman Problems. This allows us to provide high-quali...
Article
Full-text available
When performing visual servoing or object tracking tasks, active sensor planning is essential to keep targets in sight or to relocate them when missing. In particular, when dealing with a known target missing from the sensor’s field of view, we propose using prior knowledge related to contextual information to estimate its possible location. To thi...
Preprint
Full-text available
Planning safe motions for legged robots requires sophisticated safety verification tools. However, designing such tools for such complex systems is challenging due to the nonlinear and high-dimensional nature of these systems' dynamics. In this letter, we present a probabilistic verification framework for legged systems, which evaluates the safety...
Article
Full-text available
This paper proposes an online gain adaptation approach to enhance the robustness of whole-body control (WBC) framework for legged robots under unknown external force disturbances. Without properly accounting for external forces, the closed-loop control system incorporating WBC may become unstable, and therefore the desired task goals may not be ach...
Article
Full-text available
This letter presents a new control paradigm applicable to nonlinear systems such as robots subject to chance and covariance assignment constraints which we refer to as hierarchical optimal covariance control. To the best of our knowledge, this is the first study to formulate the hierarchical optimal covariance control problem involving multiple ope...
Preprint
Shared autonomy provides a framework where a human and an automated system, such as a robot, jointly control the system's behavior, enabling an effective solution for various applications, including human-robot interaction. However, a challenging problem in shared autonomy is safety because the human input may be unknown and unpredictable, which af...
Article
Full-text available
Augmenting the physical strength of a human operator during unpredictable human-directed (volitional) movements is a relevant capability for several proposed exoskeleton applications, including mobility augmentation, manual material handling, and tool operation. Unlike controllers and augmentation systems designed for repetitive tasks (e.g., walkin...
Conference Paper
Full-text available
Shared autonomy provides a framework where a human and an automated system, such as a robot, jointly control the system's behavior, enabling an effective solution for various applications, including human-robot interaction. However, a challenging problem in shared autonomy is safety because the human input may be unknown and unpredictable, which af...
Article
Full-text available
We propose a locomotion framework for bipedal robots consisting of a new motion planning method, dubbed trajectory optimization for walking robots plus (TOWR+), and a new whole-body control method, dubbed implicit hierarchical whole-body controller (IHWBC). For versatility, we consider the use of a composite rigid body (CRB) model to optimize the r...
Article
Full-text available
Automation is not a new phenomenon, and questions about its effects have long followed its advances. More than a half-century ago, US President Lyndon B. Johnson established a national commission to examine the impact of technology on the economy, declaring that automation “can be the ally of our prosperity if we will just look ahead”. In this pape...
Preprint
This paper proposes an online path planning and motion generation algorithm for heterogeneous robot teams performing target search in a real-world environment. Path selection for each robot is optimized using an information-theoretic formulation and is computed sequentially for each agent. First, we generate candidate trajectories sampled from both...
Article
Full-text available
The ability to deal with articulated objects is very important for robots assisting humans. In this work, a framework to robustly and adaptively operate common doors, using an autonomous mobile manipulator, is proposed. To push forward the state of the art in robustness and speed performance, we devise a novel algorithm that fuses a convolutional n...
Technical Report
Full-text available
Lecture notes on whole-body control for realtime control and trajectory tracking of humanoid robots under multiple contacts. This notes summarized the work of the author for the period 2007-2009.
Article
Learning from Demonstration (LfD) is a paradigm that allows robots to learn complex manipulation tasks that can not be easily scripted, but can be demonstrated by a human teacher. One of the challenges of LfD is to enable robots to acquire skills that can be adapted to different scenarios. In this paper, we propose to achieve this by exploiting the...
Preprint
Full-text available
The Short to Medium Range Autonomous Delivery System (SMADS) is a case study on developing a software stack that allows customers to request deliveries via autonomous robots on the University of Texas at Austin campus. The SMADS stack integrates several subsystems, including a robot autonomy module, a delivery scheduler, a robot interface, and a cu...
Article
Full-text available
In this work, we propose a trajectory generation method for robotic systems with contact kinematics and force constraints based on optimal control and reachability analysis tools. Normally, the dynamics and constraints of a contact-constrained robot are nonlinear and coupled to each other. Instead of linearizing the model and constraints, we solve...
Article
Full-text available
Recent experiments have shown that human joints can maintain a constant damping ratio across a wide range of external loads. This behavior can be explained by the use of a “complex stiffness” frequency-domain model approximating the impedance of the human joint. However, for a robot to replicate this naturally beneficial human behavior would requir...
Preprint
Full-text available
Model-based reinforcement learning (MBRL) algorithms can attain significant sample efficiency but require an appropriate network structure to represent system dynamics. Current approaches include white-box modeling using analytic parameterizations and black-box modeling using deep neural networks. However, both can suffer from a bias-variance trade...
Article
Full-text available
Full State Feedback (FSF) controllers for Series Elastic Actuators (SEAs) bridge the gap between impedance and admittance controllers. For humanoid robots—which must stably accomplish both stiff and soft behaviors—FSF controllers are ideal candidate joint controllers. However, previous work on FSF gain tuning has used a nonlinear passivity analysis...
Preprint
Learning from Demonstration (LfD) is a paradigm that allows robots to learn complex manipulation tasks that can not be easily scripted, but can be demonstrated by a human teacher. One of the challenges of LfD is to enable robots to acquire skills that can be adapted to different scenarios. In this paper, we propose to achieve this by exploiting the...
Article
Full-text available
The natural impedance, or dynamic relationship between force and motion, of a human operator can determine the stability of exoskeletons that use interaction-torque feedback to amplify human strength. While human impedance is typically modelled as a linear system, our experiments on a single-joint exoskeleton testbed involving 10 human subjects sho...
Preprint
The natural impedance, or dynamic relationship between force and motion, of a human operator can determine the stability of exoskeletons that use interaction-torque feedback to amplify human strength. While human impedance is typically modelled as a linear system, our experiments on a single-joint exoskeleton testbed involving 10 human subjects sho...
Preprint
Full-text available
This paper proposes an MPC-based controller to efficiently execute multiple hierarchical tasks for underactuated and constrained robotic systems. Existing task-space controllers or whole-body controllers solve instantaneous optimization problems given task trajectories and the robot plant dynamics. However, the task-space control method we propose...
Preprint
Full-text available
For a nonlinear system (e.g. a robot) with its continuous state space trajectories constrained by a linear temporal logic specification, the synthesis of a low-level controller for mission execution often results in a non-convex optimization problem. We devise a new algorithm to solve this type of non-convex problems by formulating a rapidly-explor...
Conference Paper
Full-text available
This paper proposes a method to generate feasible trajectories for robotic systems with predefined sequences of switched contacts. The proposed trajectory generation method relies on sampling-based methods, optimal control, and reachability analysis. In particular, the proposed method is able to quickly test whether a simplified model-based planner...
Article
Full-text available
Whole-body control (WBC) is a generic task-oriented control method for feedback control of loco-manipulation behaviors in humanoid robots. The combination of WBC and model-based walking controllers has been widely utilized in various humanoid robots. However, to date, the WBC method has not been employed for unsupported passive-ankle dynamic locomo...
Conference Paper
Full-text available
We present a method that finds locomanipulation plans that perform simultaneous locomotion and manipulation of objects for a desired end-effector trajectory. Key to our approach is to consider an injective locomotion constraint manifold that defines the locomotion scheme of the robot and then using this constraint manifold to search for admissible...
Article
Full-text available
In this letter, we formulate a novel Markov Decision Process (MDP) for safe and data-efficient learning for humanoid locomotion aided by a dynamic balancing model. In our previous studies of biped locomotion, we relied on a low-dimensional robot model, commonly used in high-level Walking Pattern Generators (WPGs). However, a low-level feedback cont...
Preprint
Full-text available
Endowed with higher levels of autonomy, robots are required to perform increasingly complex manipulation tasks. Learning from demonstration is arising as a promising paradigm for easily extending robot capabilities so that they adapt to unseen scenarios. We present a novel Gaussian-Process-based approach for learning manipulation skills from observ...
Preprint
When performing visual servoing or object tracking tasks, active sensor planning is essential to keep targets in sight or to relocate them when missing. In particular, when dealing with a known target missing from the sensor's field of view, we propose using prior knowledge related to contextual information to estimate its possible location. To thi...
Article
Full-text available
Five years after the DARPA Robotics Challenge (DRC) and close to the 50th anniversary of the first fullscale anthropomorphic robot developed in the world, it is our great pleasure to present the first IEEE Robotics and Automation Magazine special issue on humanoid robot applications in real-world scenarios. The aim of this special issue is to colle...
Preprint
Full-text available
Human impedance parameters play an integral role in the dynamics of strength amplification exoskeletons. Many methods are used to estimate the stiffness of human muscles, but few are used to improve the performance of strength amplification controllers for these devices. We propose a compliance shaping amplification controller incorporating an accu...
Conference Paper
Full-text available
As part of a feasibility study, this paper shows the NASA Valkyrie humanoid robot performing an end-to-end improvised explosive device (IED) response task. To demonstrate and evaluate robot capabilities, sub-tasks highlight different locomotion, manipulation, and perception requirements: traversing uneven terrain, passing through a narrow passagewa...
Preprint
Full-text available
As part of a feasibility study, this paper shows the NASA Valkyrie humanoid robot performing an end-to-end improvised explosive device (IED) response task. To demonstrate and evaluate robot capabilities, sub-tasks highlight different locomotion, manipulation, and perception requirements: traversing uneven terrain, passing through a narrow passagewa...
Conference Paper
Full-text available
As part of a feasibility study, this paper shows the NASA Valkyrie humanoid robot performing an end-to-end improvised explosive device (IED) response task. To demonstrate and evaluate robot capabilities, sub-tasks highlight different locomotion, manipulation, and perception requirements: traversing uneven terrain, passing through a narrow passagewa...
Preprint
Full-text available
In this paper, we consider the problem of verifying safety constraint satisfaction for single-input single-output systems with uncertain transfer function coefficients. We propose a new type of barrier function based on a vector norm. This type of barrier function has a measurable upper bound without full state availability. An identifier-based est...
Preprint
Full-text available
We present a method that finds locomanipulation plans that perform simultaneous locomotion and manipulation of objects for a desired end-effector trajectory. Key to our approach is to consider a generic locomotion constraint manifold that defines the locomotion scheme of the robot and then using this constraint manifold to search for admissible man...
Preprint
Full-text available
RoboCup@Home is an international robotics competition based on domestic tasks requiring autonomous capabilities pertaining to a large variety of AI technologies. Research challenges are motivated by these tasks both at the level of individual technologies and the integration of subsystems into a fully functional, robustly autonomous system. We desc...
Article
Robust Bipedal Locomotion Based on a Hierarchical Control Structure – CORRIGENDUM - Jianwen Luo, Yao Su, Lecheng Ruan, Ye Zhao, Donghyun Kim, Luis Sentis, Chenglong Fu
Preprint
This paper describes the control, and evaluation of a new human-scaled biped robot with liquid cooled viscoelastic actuators (VLCA). Based on the lessons learned from previous work from our team on VLCA [1], we present a new system design embodying a Reaction Force Sensing Series Elastic Actuator (RFSEA) and a Force Sensing Series Elastic Actuator...
Preprint
In this letter, we formulate a novel Markov Decision Process (MDP) for data efficient and safe learning for locomotion via a simplified model. In our previous studies on biped locomotion, we relied on a low-dimensional robot model, e.g., the Linear Inverted Pendulum Model (LIPM), commonly used in Walking Pattern Generators (WPG). However, employing...
Preprint
Full-text available
In this work, we propose a trajectory generation method for robotic systems with contact force constraint based on optimal control and reachability analysis. Normally, the dynamics and constraints of the contact-constrained robot are nonlinear and coupled to each other. Instead of linearizing the model and constraints, we directly solve the optimal...
Preprint
Exoskeletons which amplify the strength of their operators can enable heavy-duty manipulation of unknown objects. However, this type of behavior is difficult to accomplish; it requires the exoskeleton to sense and amplify the operator's interaction forces while remaining stable. But, the goals of amplification and robust stability when connected to...
Article
A cyberphysical avatar is a semi-autonomous robot that adjusts to an unstructured environment and performs physical tasks subject to critical timing constraints while under human supervision. This article first realizes a cyberphysical avatar that integrates three key technologies: body-compliant control, neuroevolution, and real-time constraints....
Preprint
Full-text available
With the primary objective of human-robot interaction being to support humans' goals, there exists a need to formally synthesize robot controllers that can provide the desired service. Synthesis techniques have the benefit of providing formal guarantees for specification satisfaction. There is potential to apply these techniques for devising robot...
Preprint
Human joint dynamic stiffness plays an important role in the stability of performance augmentation exoskeletons. In this paper, we consider a new frequency domain model of the human joint dynamics which features a complex value stiffness. This complex stiffness consists of a real stiffness and a hysteretic damping. We use it to explain the dynamic...
Article
Full-text available
To improve biped locomotion's robustness to internal and external disturbances, this study proposes a hierarchical structure with three control levels. At the high level, a foothold sequence is generated so that the Center of Mass (CoM) trajectory tracks a planned path. The planning procedure is simplified by selecting the midpoint between two cons...
Preprint
Full-text available
The ability to deal with articulated objects is very important for robots assisting humans. In this work a general framework for the robust operation of different types of doors using an autonomous robotic mobile manipulator is proposed. To push the state-of-the-art in robustness and speed performance, we devise a novel algorithm that fuses a convo...