Unified Push Recovery Fundamentals: Inspiration from Human Study

McGreavy, Christopher; Yuan, Kai; Gordon, Daniel; Tan, Kang; Wolfslag, Wouter; Vijayakumar, Sethu; Li, Zhibin

doi:10.1109/icra40945.2020.9196911

Cited by 6 publications

(6 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Though heuristics for energy efficient step regions are nonlinear, they can be learned by humans to achieve complex stepping behaviors. Figure 2b shows step selection during human push recovery for initial Center of Mass (CoM) push velocities from the work in [3], which are offset by mean initial velocity of non-stepping trials (0.1103 m/s) and show the stochasticity of human stepping [22,23]. In this study, our findings on the underlying optimality of stepping motions also help explain the stochasticity of human stepping.…”

Section: Introductionmentioning

confidence: 77%

See 1 more Smart Citation

Reachability Map for Diverse Balancing Strategies and Energy Efficient Stepping of Humanoids

McGreavy,

2021

Preprint

Self Cite

View full text Add to dashboard Cite

In legged locomotion, the relationship between different gait behaviors and energy consumption must consider the full-body dynamics and the robot control as a whole, which cannot be captured by simple models. This work studies the robot dynamics and whole-body optimal control as a coupled system to investigate energy consumption during balance recovery. We developed a 2-phase nonlinear optimization pipeline for dynamic stepping, which generates reachability maps showing complex energy-stepping relations. We optimize gait parameters to search all reachable locations and quantify the energy cost during dynamic transitions, which allows studying the relationship between energy consumption and stepping locations given different initial conditions. We found that to achieve efficient actuation, the stepping location and timing can have simple approximations close to the underlying optimality. Despite the complexity of this nonlinear process, we show that near-minimal effort stepping locations fall within a region of attractions, rather than a narrow solution space suggested by a simple model. This provides new insights into the non-uniqueness of near-optimal solutions in robot motion planning and control, and the diversity of stepping behavior in humans.

show abstract

Section: Introductionmentioning

confidence: 77%

“…Additionally, balance can be recovered using similar step locations and swing times for different initial CoM velocities by trading off energy optimality, which can potentially explain the large variations in step location in human study [3].…”

Section: Discussionmentioning

confidence: 99%

Reachability Map for Diverse Balancing Strategies and Energy Efficient Stepping of Humanoids

McGreavy,

2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

Section: Discussionmentioning

confidence: 99%

“…Fig. 2(b), from [8], shows step positions for human balance recovery (see Fig. 2(a)), offset by mean initial velocity of nonstepping trials (0.1103 m/s) and shows the stochasticity of human stepping [32], [33].…”

Section: Introductionmentioning

confidence: 99%

Reachability Map for Diverse and Energy Efficient Stepping of Humanoids

McGreavy

2022

IEEE/ASME Trans. Mechatron.

View full text Add to dashboard Cite

In legged locomotion, the relationship between different gait behaviors and energy consumption must consider the full-body dynamics and the robot control as a whole, which cannot be captured by simple models. This work studies the totality of robot dynamics and wholebody optimal control as a coupled system to investigate energy consumption during balance recovery. We developed a two-phase nonlinear optimization pipeline for dynamic stepping, which generates reachability maps showing complex energy-stepping relations. We optimize gait parameters to search all reachable locations and quantify the energy cost during dynamic transitions, which allows studying the relationship between energy consumption and stepping locations given different initial conditions. We found that to achieve efficient actuation, the stepping location and timing can have simple approximations close to the underlying optimality, resulting in optimal step positions with a 10.9% lower energy cost than those generated by linear inverted pendulum model. Despite the complexity of this nonlinear process, we found that near-minimal effort stepping locations are within a region of attractions, rather than a narrow solution space suggested by a simple model. This provides new insights into the nonuniqueness of nearoptimal solutions in robot motion planning and control, and the diversity of stepping behavior in humans.

show abstract

“…This demands robustness against dynamic disturbances, including modelling errors and external disturbances, and adaptability to different tasks, such as climbing stairs and crouching pass low passages. To this end, schemes that make use of various balance strategies such as the ankle, hip, stepping, and height variation strategies [1] (see Fig. 1) have been developed by the robotics community in recent years.…”

Section: Introductionmentioning

confidence: 99%

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

Ding

Xin

Lam

et al. 2021

2021 IEEE International Conference on Robotics and Automation (ICRA)

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Unified Push Recovery Fundamentals: Inspiration from Human Study

Cited by 6 publications

References 20 publications

Reachability Map for Diverse Balancing Strategies and Energy Efficient Stepping of Humanoids

Reachability Map for Diverse Balancing Strategies and Energy Efficient Stepping of Humanoids

Reachability Map for Diverse and Energy Efficient Stepping of Humanoids

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

Contact Info

Product

Resources

About