Ye Zhao

Ye Zhao
Georgia Institute of Technology | GT · School of Mechanical Engineering

Ph.D.

About

84
Publications
19,064
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
1,332
Citations
Citations since 2017
57 Research Items
794 Citations
2017201820192020202120222023050100150
2017201820192020202120222023050100150
2017201820192020202120222023050100150
2017201820192020202120222023050100150
Introduction
Ye Zhao is an Assistant Professor at The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology. He is affiliated with The Institute for Robotics and Intelligent Machines. He was a postdoc fellow at the SEAS, Harvard University. Ye obtained his Ph.D. from Mechanical Engineering, The University of Texas at Austin in 2016. Ye's research interests lie broadly in planning, control, optimization, and machine learning algorithms of highly dynamic, under-actuated, autonomous, and human-centered robots. He is especially interested in computationally efficient optimization algorithms for challenging robotics problems, for which robust, autonomous, agile, and real-time performance are formally guaranteed.
Additional affiliations
December 2011 - August 2016
University of Texas at Austin
Position
  • Graduate Associate Researcher
January 2010 - July 2011
Harbin Institute of Technology
Position
  • Student

Publications

Publications (84)
Preprint
Full-text available
Recent advancement in combining trajectory optimization with function approximation (especially neural networks) shows promise in learning complex control policies for diverse tasks in robot systems. Despite their great flexibility, the large neural networks for parameterizing control policies impose significant challenges. The learned neural contr...
Preprint
Full-text available
In this paper, we examine the problem of push recovery for bipedal robot locomotion and present a reactive decision-making and robust planning framework for locomotion resilient to external perturbations. Rejecting perturbations is an essential capability of bipedal robots and has been widely studied in the locomotion literature. However, adversari...
Preprint
Full-text available
This study proposes a hierarchically integrated framework for safe task and motion planning (TAMP) of bipedal locomotion in a partially observable environment with dynamic obstacles and uneven terrain. The high-level task planner employs linear temporal logic (LTL) for a reactive game synthesis between the robot and its environment and provides a f...
Preprint
Full-text available
In this paper, we present a versatile hierarchical offline planning algorithm, along with and an online control pipeline for agile quadrupedal locomotion. Our offline planner alternates between optimizing centroidal dynamics for a reduced-order model and whole-body trajectory optimization, with the aim of achieving dynamics consensus. Our novel mom...
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
Force modulation of robotic manipulators has been extensively studied for several decades. However, it is not yet commonly used in safety-critical applications due to a lack of accurate interaction contact modeling and weak performance guarantees - a large proportion of them concerning the modulation of interaction forces. This study presents a hig...
Preprint
Full-text available
This paper extends the family of gap-based local planners to unknown dynamic environments through generating provable collision-free properties for hierarchical navigation systems. Existing perception-informed local planners that operate in dynamic environments rely on emergent or empirical robustness for collision avoidance as opposed to providing...
Article
Full-text available
In this letter, we present a versatile hierarchical offline planning algorithm, along with an online control pipeline for agile quadrupedal locomotion. Our offline planner alternates between optimizing centroidal dynamics for a reduced-order model and whole-body trajectory optimization, with the aim of achieving dynamics consensus. Our novel moment...
Preprint
In this paper, we introduce a high-level controller synthesis framework that enables teams of heterogeneous agents to assist each other in resolving environmental conflicts that appear at runtime. This conflict resolution method is built upon temporal-logic-based reactive synthesis to guarantee safety and task completion under specific environment...
Preprint
We study the problem of refining satisfiability bounds for partially-known switched stochastic systems against planning specifications defined using syntatically co-safe Linear Temporal Logic (scLTL). We propose an abstraction-based approach that iteratively generates high-confidence Interval Markov Decision Process (IMDP) abstractions of the syste...
Article
Full-text available
Estimation of center of mass (CoM) and center of pressure (CoP) is critical for lower limb exoskeletons, prostheses, and legged robots. To meet the demand in these fields, this study presents a novel CoM and CoP estimation method for human walking through a wearable visual odometry (VO) device. This method is named VO-based estimation of CoM and Co...
Article
Full-text available
As robots move from the laboratory into the real world, motion planning will need to account for model uncertainty and risk. For robot motions involving intermittent contact, planning for uncertainty in contact is especially important, as failure to successfully make and maintain contact can be catastrophic. Here, we model uncertainty in terrain ge...
Article
We study the problem of refining satisfiability bounds for partially-known stochastic systems against planning specifications defined using syntactically co-safe Linear Temporal Logic (scLTL). We propose an abstraction-based approach that iteratively generates high-confidence Interval Markov Decision Process (IMDP) abstractions of the system from h...
Preprint
Full-text available
Reliable robotic grasping, especially with deformable objects, (e.g. fruit), remains a challenging task due to underactuated contact interactions with a gripper, unknown object dynamics, and variable object geometries. In this study, we propose a Transformer-based robotic grasping framework for rigid grippers that leverage tactile and visual inform...
Article
Full-text available
Dynamic quadrupedal locomotion over rough terrains reveals remarkable progress over the last few decades. Small-scale quadruped robots are adequately flexible and adaptable to traverse uneven terrains along the sagittal direction, such as slopes and stairs. To accomplish autonomous locomotion navigation in complex environments, spinning is a fundam...
Preprint
Full-text available
This paper takes the first step towards a reactive, hierarchical multi-robot task allocation and planning framework given a global Linear Temporal Logic specification. In our scenario, legged and wheeled robots collaborate in a heterogeneous team to accomplish a variety of navigation and delivery tasks. However, all robots are susceptible to differ...
Preprint
Full-text available
As robots move from the laboratory into the real world, motion planning will need to account for model uncertainty and risk. For robot motions involving intermittent contact, planning for uncertainty in contact is especially important, as failure to successfully make and maintain contact can be catastrophic. Here, we model uncertainty in terrain ge...
Article
Full-text available
This study proposes a Task and Motion Planning (TAMP) method with symbolic decisions embedded in a bilevel optimization. This TAMP method exploits the discrete structure of sequential manipulation for long-horizon and versatile tasks in dynamic environments. At the symbolic planning level, we propose a scalable decision-making method for long-horiz...
Preprint
Full-text available
Quadruped robots manifest great potential to traverse rough terrains with payload. Numerous traditional control methods for legged dynamic locomotion are model-based and exhibit high sensitivity to model uncertainties and payload variations. Therefore, high-performance model parameter estimation becomes indispensable. However, the inertia parameter...
Preprint
Full-text available
Dynamic quadrupedal locomotion over rough terrains, although revealing remarkable progress over the last few decades, remains a challenging task. Small-scale quadruped robots are adequately flexible and adaptable to traverse numerous uneven terrains, such as slopes and stairs, while moving along its Sagittal direction. However, spinning behaviors o...
Article
Reinforcement learning with safety constraints is promising for autonomous vehicles, of which various failures may result in disastrous losses. In general, a safe policy is trained by constrained optimization algorithms, in which the average constraint return as a function of states and actions should be lower than a predefined bound. However, most...
Preprint
Full-text available
As robots move from the laboratory into the real world, motion planning will need to account for model uncertainty and risk. For robot motions involving intermittent contact, planning for uncertainty in contact is especially important, as failure to successfully make and maintain contact can be catastrophic. Here, we model uncertainty in terrain ge...
Article
Full-text available
Overhead manipulation often needs collaboration of two operators, which is challenging in confined space such as in a compartment or on a ladder. Supernumerary Robotic Limb (SuperLimb), as a promising wearable robotics solution for overhead tasks, can provide optimal assistance in terms of broader workspace, diverse manipulation functionalities, an...
Article
Trajectory optimization with contact-rich behaviors has recently gained attention for generating diverse locomotion behaviors without pre-specified ground contact sequences. However, these approaches rely on precise models of robot dynamics and the terrain and are susceptible to uncertainty. Recent works have attempted to handle uncertainties in th...
Preprint
Full-text available
This study proposes a Task and Motion Planning (TAMP) method with symbolic decisions embedded in a bilevel optimization. This TAMP method exploits the discrete structure of sequential manipulation for long-horizon and versatile tasks in dynamically changing environments. At the symbolic planning level, we propose a scalable decision-making method f...
Preprint
Full-text available
Trajectory optimization with contact-rich behaviors has recently gained attention for generating diverse locomo-tion behaviors without pre-specified ground contact sequences. However, these approaches rely on precise models of robot dynamics and the terrain and are susceptible to uncertainty. Recent works have attempted to handle uncertainties in t...
Preprint
Full-text available
This study proposes an integrated task and motion planning method for dynamic locomotion in partially observable environments with multi-level safety guarantees. This layered planning framework is composed of a high-level symbolic task planner and a low-level phase-space motion planner. A belief abstraction at the task planning level enables belief...
Conference Paper
Full-text available
This study proposes an integrated task and motion planning method for dynamic locomotion in partially observable environments with multi-level safety guarantees. This layered planning framework is composed of a high-level symbolic task planner and a low-level phase-space motion planner. A belief abstraction at the task planning level enables belief...
Preprint
Full-text available
Force modulation of robotic manipulators has been extensively studied for several decades but is not yet commonly used in safety-critical applications due to a lack of accurate interaction contact modeling and weak performance guarantees - a large proportion of them concerning the modulation of interaction forces. This study presents a high-level f...
Preprint
Full-text available
Trajectory optimization is becoming increasingly powerful in addressing motion planning problems of underactuated robotic systems. Numerous prior studies solve such a class of large non-convex optimal control problems in a hierarchical fashion. However, numerical accuracy issues are prone to occur when one uses a full-order model to track reference...
Conference Paper
Full-text available
Trajectory optimization is becoming increasingly powerful in addressing motion planning problems of under-actuated robotic systems. Numerous prior studies solve such a class of large non-convex optimal control problems in a hierarchical fashion. However, significant inaccuracy issues are prone to occur when one uses a full-order model to track refe...
Conference Paper
Full-text available
We present planning and control techniques for non-periodic locomotion tasks specified by temporal logic in rough cluttered terrains. Our planning approach is based on a discrete set of motion primitives for the center of mass (CoM) of a general bipedal robot model. A deterministic shortest path problem is solved over the Büchi automaton of the tem...
Conference Paper
Full-text available
Dynamic legged locomotion is being explored as a means to maneuver on rugged and unstructured terrains. However, limited foot contact sensing capabilities often prohibit bipedal robots from being deployed on complex terrains. Locomotion over cluttered outdoor environments requires the contacting foot to be aware of terrain geometries, stiffness, an...
Article
Full-text available
This study proposes an integrated planning and control framework for achieving three-dimensional robust and dynamic legged locomotion over uneven terrain. The proposed framework is composed of three hierarchical layers. The high-level layer is a state-space motion planner designing highly dynamic locomotion behaviors based on a reduced-order robot...
Article
This paper proposes a tube-based method for the asynchronous observation problem of discrete-time switched linear systems in the presence of amplitude-bounded disturbances. Sufficient stability conditions of the nominal observer error system under mode-dependent persistent dwell-time (MPDT) switching are first established. Taking the disturbances i...
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
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
Robotic systems are increasingly relying on distributed feedback controllers to tackle complex and latency-prone sensing and decision problems. These demands come at the cost of a growing computational burden and, as a result, larger controller latencies. To maximize robustness to mechanical disturbances and achieve high control performance, we emp...
Preprint
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...
Article
Full-text available
This study investigates the problem of dynamic walking impact on a biped robot. Two online variable stiffness control algorithms, i.e., torque balance algorithm (TBA) and surface fitting algorithm (SFA), are proposed based on virtual spring leg to achieve compliant performance. These two algorithms target on solving the high nonlinearity commonly e...
Conference Paper
Full-text available
In this paper, whole body operational space (WBOS) framework for three dimensional passive-foot biped robot is presented. The stability of WBOS controller is analyzed and a foot placement planner is proposed. In many cases, WBOS controller generates torque commands to execute the trajectories planned by high-level planners every control loop. The p...
Article
Full-text available
Series elastic actuators (SEAs) are becoming commonplace in torque-controlled robots to achieve compliant interactions with both environments and humans. However, designing high-performance impedance controllers and characterizing performance for SEAs with time delays and electronic filters are under-explored problems. The presented study addresses...
Article
Full-text available
This study presents a theoretical method for planning and controlling agile bipedal locomotion based on robustly tracking a set of non-periodic keyframe states. Based on centroidal momentum dynamics, we formulate a hybrid phase-space planning and control method which includes the following key components: (i) a step transition solver that enables d...
Article
Full-text available
Humanoid robots are increasingly demanded to operate in interactive and human-surrounded environments while achieving sophisticated locomotion and manipulation tasks. To accomplish these tasks, roboticists unremittingly seek for advanced methods that generate whole-body coordination behaviors and meanwhile fulfill various planning and control objec...
Conference Paper
Full-text available
Contact-based decision and planning methods are increasingly being sought for task execution in humanoid robots. However, formal methods from the verification and synthesis communities have not been yet incorporated into the motion planning sequence for complex mobility behaviors in humanoid robots. This study takes a step toward formally synthesiz...
Conference Paper
Full-text available
Whole-Body Control has been extensively used to achieve humanoid robot force and motion tasks simultaneously during recent years. However, most existing results have not incorporated low-level actuator dynamics and time delays yet. In this study, we propose a novel time-delayed Whole-Body Operational Space control (WBOSC) with series elastic actuat...
Article
Full-text available
Whole-body operational space controllers (WBOSCs) are versatile and well suited for simultaneously controlling motion and force behaviors, which can enable sophisticated modes of locomotion and balance. In this paper, we formulate a WBOSC for point-foot bipeds with series-elastic actuators (SEA) and experiment with it using a teen-size SEA biped ro...
Conference Paper
Full-text available
In this study, we present a framework for phase- space planning and control of agile bipedal locomotion while robustly tracking a set of non-periodic keyframes. By using a reduced-order model, we formulate a hybrid planning framework where the center-of-mass motion is constrained to a general surface manifold. This framework also proposes phase-spa...