Design, analysis and control of the series-parallel hybrid RH5 humanoid robot

Eber, Julian; Kumar, Shivesh; Peters, Heiner; Bargsten, Vinzenz; Fernández, José de Gea; Mastalli, Carlos; Stasse, Olivier; Kirchner, Frank

doi:10.1109/humanoids47582.2021.9555770

Cited by 11 publications

(7 citation statements)

References 18 publications

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“…The comparison across all these problems is unusual, and it represents an important contribution to the research community since we have open sourced many of these examples, as well as the Box-FDDP algorithm, in the Crocoddyl repository (Mastalli et al, 2019). Our feasibility-driven approach enabled model predictive control applications on the ANYmal C robot, however, it can potentially be used in other applications such as in humanoid robotics (Eßer et al, 2021), robot co-design (IROS, 2022), and learning (Lembono et al, 2020). describe the tasks, where each way-point specifies the desired pose and velocity.…”

Section: Discussionmentioning

confidence: 99%

A feasibility-driven approach to control-limited DDP

et al. 2022

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Differential dynamic programming (DDP) is a direct single shooting method for trajectory optimization. Its efficiency derives from the exploitation of temporal structure (inherent to optimal control problems) and explicit roll-out/integration of the system dynamics. However, it suffers from numerical instability and, when compared to direct multiple shooting methods, it has limited initialization options (allows initialization of controls, but not of states) and lacks proper handling of control constraints. In this work, we tackle these issues with a feasibility-driven approach that regulates the dynamic feasibility during the numerical optimization and ensures control limits. Our feasibility search emulates the numerical resolution of a direct multiple shooting problem with only dynamics constraints. We show that our approach (named Box-FDDP) has better numerical convergence than Box-DDP$$^+$$ + (a single shooting method), and that its convergence rate and runtime performance are competitive with state-of-the-art direct transcription formulations solved using the interior point and active set algorithms available in Knitro. We further show that Box-FDDP decreases the dynamic feasibility error monotonically—as in state-of-the-art nonlinear programming algorithms. We demonstrate the benefits of our approach by generating complex and athletic motions for quadruped and humanoid robots. Finally, we highlight that Box-FDDP is suitable for model predictive control in legged robots.

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Section: Discussionmentioning

confidence: 99%

A feasibility-driven approach to control-limited DDP

et al. 2022

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“…Complex humanoid robots such as Atlas successfully achieved balance and control in motion planning and locomotion by combining the full kinematic model with a reduced dynamic model (e.g., CoM, CoP) of the robot instead of the full dynamics, which could be computationally prohibitive in solving trajectory optimization. The analysis and control of the RH5 humanoid robot in [132] is based on differential dynamic programming (DDP). The full-body trajectory optimization of RH5 showcased contact stability with DDP while generating walking trajectories using the classical control technique (Proportional-Derivative) position control.…”

Section: Discussionmentioning

confidence: 99%

“…Robot Operating System (ROS) description format files such as Unified Robot Description Format (URDF) and Simulation Description Format (SDF) [130] are loaded as inputs, which give the robot's physical description for the rigid robot system to be modeled using the modeling tools. These tools have been used in the design of humanoid robots [131,132] and also in exoskeletons for human walking [28,124]. Series-parallel hybrid designs for, e.g., Recupera Exoskeleton (see Figure 9) have large degrees of freedom in their spanning tree and computing the complete kinematic and dynamic models can be computationally expensive.…”

Section: Modeling Toolsmentioning

confidence: 99%

“…To guarantee safety at this level, it is important to consider the limitations of positions, velocities, and torque of every human joint as well as the exoskeleton system at the level of trajectory design and feedback control. Advanced trajectory optimization methods usually offer such possibilities either as soft or hard constraints [132,169].…”

Section: Control and Safetymentioning

confidence: 99%

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A Survey on Design and Control of Lower Extremity Exoskeletons for Bipedal Walking

2022

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Exoskeleton robots are electrically, pneumatically, or hydraulically actuated devices that externally support the bones and cartilage of the human body while trying to mimic the human movement capabilities and augment muscle power. The lower extremity exoskeleton device may support specific human joints such as hip, knee, and ankle, or provide support to carry and balance the weight of the full upper body. Their assistive functionality for physically-abled and disabled humans is demanded in medical, industrial, military, safety applications, and other related fields. The vision of humans walking with an exoskeleton without external support is the prospect of the robotics and artificial intelligence working groups. This paper presents a survey on the design and control of lower extremity exoskeletons for bipedal walking. First, a historical view on the development of walking exoskeletons is presented and various lower body exoskeleton designs are categorized in different application areas. Then, these designs are studied from design, modeling, and control viewpoints. Finally, a discussion on future research directions is provided.

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“…In this work, we present an experimental study to demonstrate for the first time that it is possible to employ a high-frequency motion capture system for online stabilization of the humanoid robot RH5 [11]. We use motion capture as an alternative for proprioceptive state estimation.…”

Section: Introductionmentioning

confidence: 99%

Experimental Investigations into Using Motion Capture State Feedback for Real-Time Control of a Humanoid Robot

Popescu

Mronga

Bergonzani

et al. 2022

Sensors

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Regardless of recent advances, humanoid robots still face significant difficulties in performing locomotion tasks. Among the key challenges that must be addressed to achieve robust bipedal locomotion are dynamically consistent motion planning, feedback control, and state estimation of such complex systems. In this paper, we investigate the use of an external motion capture system to provide state feedback to an online whole-body controller. We present experimental results with the humanoid robot RH5 performing two different whole-body motions: squatting with both feet in contact with the ground and balancing on one leg. We compare the execution of these motions using state feedback from (i) an external motion tracking system and (ii) an internal state estimator based on inertial measurement unit (IMU), forward kinematics, and contact sensing. It is shown that state-of-the-art motion capture systems can be successfully used in the high-frequency feedback control loop of humanoid robots, providing an alternative in cases where state estimation is not reliable.

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Design, analysis and control of the series-parallel hybrid RH5 humanoid robot

Cited by 11 publications

References 18 publications

A feasibility-driven approach to control-limited DDP

A feasibility-driven approach to control-limited DDP

A Survey on Design and Control of Lower Extremity Exoskeletons for Bipedal Walking

Experimental Investigations into Using Motion Capture State Feedback for Real-Time Control of a Humanoid Robot

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