Project

Legged Locomotion

Goal: Aiming to study the robust whole body control

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Project log

Jianwen Luo
added 2 research items
Quadruped robots manifest great potential to traverse rough terrains with payload. Current model-based controllers, which are extensively adopted in quadruped robot locomotion control, rely on accurate estimation of parameters and will significantly deteriorate in severe disturbance, e.g., adding heavy payload. This study introduces an online identification method, which is named as Adaptive Control for Quadruped Locomotion (ACQL), to address model uncertainties. Meanwhile, a concurrent adaptive controller is also indispensable to accomplish identification and locomotion. Therefore, this study presents an adaptive control algorithm based on the online payload identification for the high payload capacity (the ratio between payload and robot's self-weight) quadruped locomotion. The newly proposed algorithm could achieve estimating and compensating the external disturbances induced by the payload online. The tracking accuracy of the robot's Center of Mass (CoM) and orientation trajectories for the identification task is highly improved. The locomotion task can be incorporated in inverse-dynamics-based Quadratic Programming (QP), realizing a trotting gait. The proposed method is verified in a real quadruped robot platform. Experiments prove the estimation efficacy for the payload weighing from 20 kg to 75 kg and loaded at different locations of the robot's torso.
Ye Zhao
added a research item
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, adversarial disturbances and aggressive turning can lead to negative lateral step width (i.e., crossed-leg scenarios) with unstable motions and self-collision risks. These motion planning problems are computationally difficult and have not been explored under a hierarchically integrated task and motion planning method. We explore a planning and decision-making framework that closely ties linear-temporal-logic-based reactive synthesis with trajec-tory optimization incorporating the robot's full-body dynamics, kinematics, and leg collision avoidance constraints. Between the high-level discrete symbolic decision-making and the low-level continuous motion planning, behavior trees serve as a reactive interface to handle perturbations occurring at any time of the locomotion process. Our experimental results show the efficacy of our method in generating resilient recovery behaviors in response to diverse perturbations from any direction with bounded magnitudes.
Jianwen Luo
added a research item
With the gradual maturity of the software and hardware of quadruped robots, the application scenarios of quadruped robots are increasing, such as security, rescue, exploration and other tasks. Quadruped robots are flexible and adaptive to challenging or complex environment. This study presents a large-scale quadruped robot, Pegasus II, which is a new version upgraded from the previous quadruped robot, Pegasus. System design of Pegasus II is introduced, including mechanical and electronic design. Locomotion control for a special scene, L-shaped narrow corner, in which a large-scale quadruped robot is not able to traverse in a common quadrupedal mode, is demonstrated. The long body length of a large-scale quadruped robot, such as Pegasus II, incurs difficulty in traversing freely in such a narrow passage. Motivated by this issue, this study proposes an experimental implementation to realize the transition from quadrupedal mode to bipedal mode. The control framework is presented, which mainly includes trajectory optimization, whole-body control, compliance control, and joint torque estimator. Simulations and experiments are conducted to validate the performance, including gait transition, compliance control.
Chenglong Fu
added a research item
Compliance is important for humanoid robots, especially a position-controlled one, to perform tasks in complicated environments where unexpected or sudden contacts will result in large impacts which may cause instability or destroy the hardware of robots. This paper presents a compliance control method based on viscoelastic model for humanoid robots to survive on these conditions. The viscoelastic model is used to obtain the relationship between the differential of contact force/torque and linear/angular position. Thus a state equation of this model can be established and a state feedback controller adjusting the position to adapt to the contact force/torque can be designed to realize the compliant movement. The proposed compliance control method based on viscoelastic model has been employed in ankle compliance for stable walking on indefinite uneven terrain and arm compliance for falling protection on BHR-6P, a position-controlled humanoid robot, which validates its effectiveness.
Jianwen Luo
added a project goal
Aiming to study the robust whole body control
 
Jianwen Luo
added a research item
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 CoP (VOECC). The methodology of VOECC is that the VO provides CoM trajectory estimation and the inherent walking dynamics model is exploited as prior knowledge for CoP trajectory estimation during human walking. Gait cycle is estimated based on the frequency analysis of the CoM trajectory, which is cropped into segments. Each segment mainly includes a half gait cycle. The segments are designed to be sliding to mitigate the disturbance of double-stance phase. For each segment, a quadratic programming (QP) problem is formulated to fit the CoM measurement with the theoretical walking dynamics model. The solution to this QP problem is an optimal gait parameters estimation, including CoP. Based on this solution, the human walking model with the CoM trajectory and CoP excursion is reconstructed. VOECC is evaluated experimentally where human walks on level ground and upstairs with VO device attached in front of the chest. The ground truth of CoM and CoP position is directly measured by the motion capture system and fully instrumented treadmill, respectively, and compared with the VOECC results. The proposed method is demonstrated to be effective in terms of wearable and extensible functionalities compared with the existing methods. Root-mean-squared errors between the CoP measured by fully instrumented treadmill and the CoP estimated by VOECC are evaluated and compared. This method has the potential to be extensible in lower limb rehabilitation, prosthetic, and legged locomotion fields.
Jianwen Luo
added 5 research items
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 locomotion. As such, in this article, we devise a new WBC, dubbed the whole-body locomotion controller (WBLC), that can achieve experimental dynamic walking on unsupported passive-ankle biped robots. A key aspect of WBLC is the relaxation of contact constraints such that the control commands produce reduced jerk when switching foot contacts. To achieve robust dynamic locomotion, we conduct an in-depth analysis of uncertainty for our dynamic walking algorithm called the time-to-velocity-reversal (TVR) planner. The uncertainty study is fundamental as it allows us to improve the control algorithms and mechanical structure of our robot to fulfill the tolerated uncertainty. In addition, we conduct extensive experimentation for: (1) unsupported dynamic balancing (i.e., in-place stepping) with a six-degree-of-freedom biped, Mercury; (2) unsupported directional walking with Mercury; (3) walking over an irregular and slippery terrain with Mercury; and 4) in-place walking with our newly designed ten-DoF viscoelastic liquid-cooled biped, DRACO. Overall, the main contributions of this work are on: (a) achieving various modalities of unsupported dynamic locomotion of passive-ankle bipeds using a WBLC controller and a TVR planner; (b) conducting an uncertainty analysis to improve the mechanical structure and the controllers of Mercury; and (c) devising a whole-body control strategy that reduces movement jerk during walking.
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 planners find the trajectories by watching the behaviors of longer time horizon. Instead, our planner updates a step location every control loop by watching the center-of-mass (CoM) state to achieve robust balancing. The robustness is also enhanced because contact events vary the stance leg switching time from the given nominal step frequency. Via this new foot placement planner, the locomotion's robustness to unknown terrains is improved. Dynamically stable walking on flat and unknown terrains, and push recovery are tested in real-time dynamic simulation.
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 locomotion. As such, in this paper, we devise a new WBC, dubbed whole-body locomotion controller (WBLC), that can achieve experimental dynamic walking on unsupported passive-ankle biped robots. A key aspect of WBLC is the relaxation of contact constraints such that the control commands produce reduced jerk when switching foot contacts. To achieve robust dynamic locomotion, we conduct an in-depth analysis of uncertainty for our dynamic walking algorithm called time-to-velocity-reversal (TVR) planner. The uncertainty study is fundamental as it allows us to improve the control algorithms and mechanical structure of our robot to fulfill the tolerated uncertainty. In addition, we conduct extensive experimentation for: 1) unsupported dynamic balancing (i.e. in-place stepping) with a six degree-of-freedom (DoF) biped, Mercury; 2) unsupported directional walking with Mercury; 3) walking over an irregular and slippery terrain with Mercury; and 4) in-place walking with our newly designed ten-DoF viscoelastic liquid-cooled biped, DRACO. Overall, the main contributions of this work are on: a) achieving various modalities of unsupported dynamic locomotion of passive-ankle bipeds using a WBLC controller and a TVR planner, b) conducting an uncertainty analysis to improve the mechanical structure and the controllers of Mercury, and c) devising a whole-body control strategy that reduces movement jerk during walking.