Jiatao Ding

Delft University of Technology

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Xiaohui Xiao

Wuhan University

Cosimo Della Santina

Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)

Jens Kober

Delft University of Technology

Nikos G. Tsagarakis

Italian Institute of Technology

Chengxu Zhou

University College London

Yang Wang

ShanghaiTech University

Vassil Atanassov

University of Oxford

Jiajia Chen

Shanghai Jiao Tong University

Jianxin Pang

Shenzhen Academy of Robotics

Chip-Hong Chang

Nanyang Technological University

Cooperative Institutions

Wuhan University

Delft University of Technology

Chinese Academy of Sciences

Shenzhen Academy of Robotics

Singapore University of Technology and Design

Italian Institute of Technology

Shenzhen Institutes of Advanced Technology

University of Leeds

University of Edinburgh

Nanjing University of Aeronautics and Astronautics

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Nonlinear optimization of Step Duration and Step Location

2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2019)

Jiatao Ding Xiaohui Xiao Nikos G. Tsagarakis

The modulation of step location and duration plays an important role in realizing robust bipedal walking. This paper formulates it as a nonlinear programming problem (NLP) and proposes a novel optimization approach to adjust step location and duration in real time. Based on state feedback, the Linear Inverted Pendulum dynamics is exploited to determine the optimal step parameters. Different from previous works, this work presents three main characteristics: i) the hyperbolic functions of step duration rather than the step duration itself are chosen to be optimization variables; ii) the approach can be switched from baseline two-steps-prediction optimization to one-step-prediction optimization through merely adding several equality constraints in problem formulation; iii) the approach can deal with relative step location tracking (velocity tracking) or absolute step location tracking (position tracking) via changing the reference step parameters. As a result, the first characteristic enables the NLP to be solved in a computational-efficient manner and the latter two endow the approach with versatility under different control modes. The effectiveness has been demonstrated by simulation experiments.

Position (finance)

Tracking (education)

Two step

10.1109/iros40897.2019.8968229

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Citations (10)

A Novel Optimization Design of Dual-Slide Parallel Elastic Actuator for Legged Robots

IEEE/ASME Transactions on Mechatronics (2024)

Siyu Liu Jiatao Ding Chunlei Lu Zhirui Wang Bo Su

The usage of parallel elastic actuators (PEA) in legged robots could potentially enhance the joints and increase energy efficiency by providing extra torques. However, the current design that adopts tension springs or spiral springs usually requires additional working space for PEA add-ons and enlarges size and mass too much. Besides, they often tune the spring parameters especially the spring constant by hand, failing to achieve optimal performance when considering multiple objectives. To tackle these issues, this article designs a compact dual-slide PEA (DS-PEA) leg that adopts a compression spring structure. Through integrating with a dual-slide mechanism, the PEA elements are attached tightly to the transmission, resulting in a small-size and light-weighted design. Furthermore, we adopt a multiobjective optimization method, i.e., multi-Pareto fronts quantify, to automatically choose the proper spring constant. Simulation and hardware experiments demonstrate that peak torque, motor power, and cost of transport for motion tracking are all largely reduced, even when working at multiple trajectories. Extensive hopping experiments further validate the dynamic motion capability and the energy efficiency of the delicate design. The compact DS-PEA leg will be used in a quadruped robot shortly.

10.1109/tmech.2024.3401546

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Nonlinear model predictive control for robust bipedal locomotion: exploring angular momentum and CoM height changes

Advanced Robotics (2021)

Jiatao Ding Chengxu Zhou Xin Song Xiaohui Xiao Nikos G. Tsagarakis

Human beings can utilize multiple balance strategies, e.g. step location adjustment and angular momentum adaptation, to maintain balance when walking under dynamic disturbances. In this work, we propose a novel Nonlinear Model Predictive Control (NMPC) framework for robust gait pattern generation, with the capabilities of step location adjustment, Center of Mass (CoM) height variation, and angular momentum adaptation. These features are realized by constraining the Zero Moment Point within the support polygon. By employing the nonlinear inverted pendulum plus flywheel model, the effects of upper-body rotation and vertical height motion are considered. As a result, the NMPC is formulated as a quadratically constrained quadratic program problem, which is solved fast by sequential quadratic programming. Consequently, robust walking patterns that exploit reactive stepping, body inclination, and CoM height variation are generated. Adaptable walking in multiple scenarios has been demonstrated through simulation studies.

Model Predictive Control

Sequential quadratic programming

Zero moment point

Moment of inertia

Flywheel

Pendulum

10.1080/01691864.2021.1928543

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Citations (11)

Robust real-time walking pattern generation with dynamical consistency: An analytical method combined with optimal solution

2021 IEEE International Conference on Robotics and Biomimetics (ROBIO) (2017)

Jiatao Ding Minghui Yang Jiangchen Zhou Daojin Yao Xiaohui Xiao

This paper proposes a novel method toward real-time walking pattern generation with guaranteeing the dynamical consistency during the whole cycle. Extending the conventional Linear Inverted Pendulum Model (LIPM), this paper takes the dynamics of the Double Support Phase (DSP) into consideration. Considering the Zero-Moment-Point (ZMP) movement during the DSP, the reference ZMP trajectory is first planned. Then the Center of Mass (CoM) trajectory is obtained by analytically solving the differential equation derived from LIPM. To determine the boundary conditions, an offline numerical optimization algorithm is utilized. Furthermore, in order to enhance the robustness, the sudden change of step location and timing should be considered. With guaranteeing the dynamical continuity, a Quadratic Programming (QP) problem with equality constraints is proposed and solved to obtain the CoM trajectory during the current Single Support Phase (SSP). For bipedal walking with or without the sudden adjustment of step location and timing, the simulation and hardware experiments have been done to demonstrate the effectiveness.

Robustness

Zero moment point

Trajectory Optimization

10.1109/robio.2017.8324680

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Citations (1)

Energy-Efficient Bipedal Gait Pattern Generation via CoM Acceleration Optimization

Jiatao Ding Chengxu Zhou Xiaohui Xiao

Energy consumption for bipedal walking plays a central role for a humanoid robot with limited battery capacity. Studies have revealed that exploiting the allowable Zero Moment Point region (AZR) and Center of Mass (CoM) height variation (CoMHV) are strategies capable of improving energy performance. In general, energetic cost is evaluated by integrating the electric power of multi joints. However, this Joint-Power-based Index requires computing joint torques and velocities in advance, which usually requires time-consuming iterative procedures, especially for multi-joints robots. In this work, we propose a CoM-Acceleration-based Optimal Index (CAOI) to synthesize an energetically efficient CoM trajectory. The proposed method is based on the Linear Inverted Pendulum Model, whose energetic cost can be easily measured by the input energy required for driving the point mass to track a reference trajectory. We characterize the CoM motion for a single walking cycle and define its energetic cost as Unit Energy Consumption. Based on the CAOI, an analytic solution for CoM trajectory generation is provided. Hardware experiments demonstrated the computational efficiency of the proposed approach and the energetic benefits of exploiting AZR and CoMHV strategies.

10.1109/humanoids.2018.8625042

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Citations (8)

Correction to: Walking Stabilization Control for Humanoid Robots on Unknown Slope Based on Walking Sequences Adjustment

Journal of Intelligent & Robotic Systems (2018)

Jiatao Ding Yang Wang Minghui Yang Xiaohui Xiao

Foundation (evidence)

Line (geometry)

10.1007/s10846-018-0784-x

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Versatile Locomotion by Integrating Ankle, Hip, Stepping, and Height Variation Strategies

Jiatao Ding Songyan Xin Tin Lun Lam Sethu Vijayakumar

Stable walking in real-world environments is a challenging task for humanoid robots, especially when considering the dynamic disturbances, e.g., caused by external perturbations that may be encountered during locomotion. The varying nature of disturbance necessitates high adaptability. In this paper, we propose an enhanced Nonlinear Model Predictive Control (NMPC) approach for robust and adaptable walking – we term it versatile locomotion, by limiting both the Center of Pressure (CoP) and Divergent Component of Motion (DCM) movements. Due to utilization of the Nonlinear Inverted Pendulum plus Flywheel model, the robot is endowed with the capabilities of CoP manipulation (if equipped with finitesized feet), step location adjustment, upper body rotation, and vertical height variation. Considering the feasibility constraints, especially the usage of relaxed CoP constraints, the NMPC scheme is established as a Quadratically Constrained Quadratic Programming problem, which is solved efficiently by Sequential Quadratic Programming with enhanced solvability. Simulation experiments demonstrate the effectiveness of our method to recruit optimal hybrid strategies in order to realize versatile locomotion, for the robot with finite-sized or point feet.

Sequential quadratic programming

Robot locomotion

Model Predictive Control

10.1109/icra48506.2021.9561130

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Citations (6)

Periodic Stability for 2-D Biped Dynamic Walking on Compliant Ground

Lecture notes in computer science (2015)

Yang Wang Jiatao Ding Xiaohui Xiao

Ground reaction force

10.1007/978-3-319-22876-1_32

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Citations (6)

Energy-Efficient Bipedal Walking: From Single-Mass Model to Three-Mass Model

Robotica (2021)

Jiatao Ding Jiangchen Zhou Zhao Guo Xiaohui Xiao

SUMMARY The work aims to realize energy-efficient bipedal walking by employing the three-mass inverted pendulum model (3MIPM) and compare its energy performance with linear inverted pendulum model (LIPM). To do this, a general optimal index on center of mass (CoM) acceleration is first derived for energetic cost evaluation. After defining the equivalent zero moment point (ZMP) motion, an unconstrained optimization approach for CoM generation is extended for 3MIPM, which can track different ZMP references and address the height variation as well. To make use of the allowable ZMP movement, a constrained optimization method is also employed, contributing to lower energetic cost. Simulation and hardware experiments on a humanoid robot demonstrate that the 3MIPM could achieve higher energy efficiency.

Zero moment point

10.1017/s0263574720001320

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Citations (1)

Quadrupedal Locomotion With Parallel Compliance: E-Go Design, Modeling, and Control

IEEE/ASME Transactions on Mechatronics (2024)

Jiatao Ding Perry Posthoorn Vassil Atanassov Fabio Boekel Jens Kober

Quadrupedalism

10.1109/tmech.2024.3402321

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Citations (0)