TRBR: Flight body posture compensation for transverse ricochetal brachiation robot

Lin, Chi-Ying; Yang, Zong-Han

doi:10.1016/j.mechatronics.2019.102307

Cited by 8 publications

(14 citation statements)

References 12 publications

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“…The numerical values of model parameters were obtained using CAD software (see Table 3 ). The parameters of the DC motors were obtained using a system identification process [ 8 ].…”

Section: Locomotion Control For Transverse Ledge Brachiationmentioning

confidence: 99%

“…Transverse ledge-climbing robots are a form of bio-inspired climbing robots [ 1 , 2 , 3 , 4 , 5 , 6 , 7 ] mimicking the movement of climbers traversing ledges on a vertical wall [ 8 ]. They can be used to perform dangerous or labor-intensive tasks, such as surveillance, inspection, rescue, and maintenance [ 9 , 10 , 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

“…Transverse brachiation refers to a swinging movement between ledges on a wall, during which the body is alternately supported under each forelimb. In situations where handholds are beyond the reach of the robot (i.e., non-continuous ledges), the energy stored during the swing phase can be used to leap toward the target ledge (i.e., transverse ricochetal brachiation) [ 8 ]. Note that this requires posture compensation during the flight phase to minimize bounce during landing as well as sophisticated eye-hand coordination.…”

Section: Introductionmentioning

confidence: 99%

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Design of Transverse Brachiation Robot and Motion Control System for Locomotion between Ledges at Different Elevations

Lin

Yongjie

2022

Sensors

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Bio-inspired transverse brachiation robots mimic the movement of human climbers as they traverse along ledges on a vertical wall. The constraints on the locomotion of these robots differ considerably from those of conventional brachiation robots due primarily to the need for robust hand-eye coordination. This paper describes the development of a motion control strategy for a brachiation robot navigating between wall ledges positioned on a level plane or at different elevations. We based our robot on a four-link arm-body-tail system performing a four-phase movement, including a release phase, body reversal phase, swing-up phase, and grasping phase. We designed a gripper that uses passive wrist joint motion to grasp the ledge during the tail swing. We also developed a dynamic model by which to coordinate the swing-up movement, define the phase switching conditions, and time the grasping action of the grippers. In experiments, the robot proved highly effective in traversing between wall ledges of the same or different elevations.

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“…The numerical values of model parameters were obtained using CAD software (see Table 3 ). The parameters of the DC motors were obtained using a system identification process [ 8 ].…”

Section: Locomotion Control For Transverse Ledge Brachiationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Design of Transverse Brachiation Robot and Motion Control System for Locomotion between Ledges at Different Elevations

Lin

Yongjie

2022

Sensors

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“…Transverse ledge brachiation robots are bio-inspired climbing robots that mimic climbing athletes [ 1 , 2 , 3 ]. They move sideways across walls by grabbing wall protrusions [ 4 ], swinging their lower limb(s), and using alternating handholds.…”

Section: Introductionmentioning

confidence: 99%

Multi-Locomotion Design and Implementation of Transverse Ledge Brachiation Robot Inspired by Sport Climbing

Lin

Lee

2023

Biomimetics

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Brachiation robots mimic the locomotion of bio-primates, including continuous brachiation and ricochetal brachiation. The hand-eye coordination involved in ricochetal brachiation is complex. Few studies have integrated both continuous and ricochetal brachiation within the same robot. This study seeks to fill this gap. The proposed design mimics the transverse movements of sports climbers holding onto horizontal wall ledges. We analyzed the cause-and-effect relationship among the phases of a single locomotion cycle. This led us to apply a parallel four-link posture constraint in model-based simulation. To facilitate smooth coordination and efficient energy accumulation, we derived the required phase switching conditions as well as joint motion trajectories. Based on a two-hand-release design, we propose a new style of transverse ricochetal brachiation. This design better exploits inertial energy storage for enhanced moving distance. Experiments demonstrate the effectiveness of the proposed design. A simple evaluation method based on the final robot posture from the previous locomotion cycle is applied to predict the success of subsequent locomotion cycles. This evaluation method serves as a valuable reference for future research.

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“…[16][17][18][19] The con¯rmation of the global stability and of convergence to an optimum for such control methods remains a challenge. [20][21][22] This research area remains open for further advancements and additional results on the control of brachiate and bi-brachiate robots can be found in Refs. 23-29. In this paper, a novel nonlinear optimal (H-in¯nity) control method is developed for multi-DOF underactuated brachiation robots.…”

Section: Introductionmentioning

confidence: 99%

A Nonlinear Optimal Control Approach for Multi-DOF Brachiation Robots

Rigatos

Abbaszadeh

Busawon

et al. 2021

Int. J. Human. Robot.

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This paper proposes a nonlinear optimal control approach for mulitple degrees of freedom (DOF) brachiation robots, which are often used in inspection and maintenance tasks of the electric power grid. Because of the nonlinear and multivariable structure of the related state-space model, as well as because of underactuation, the control problem of these robots is nontrivial. The dynamic model of the brachiation robots undergoes first approximate linearization with the use of Taylor series expansion around a temporary operating point which is recomputed at each iteration of the control method. For the approximately linearized model, an H-infinity feedback controller is designed. The linearization procedure relies on the Jacobian matrices of the brachiation robots’ state-space model. The proposed control method stands for the solution of the optimal control problem for the nonlinear and multivariable dynamics of the brachiation robots, under model uncertainties and external perturbations. For the computation of the controller’s feedback gains an algebraic Riccati equation is solved at each time-step of the control method. The global stability properties of the control scheme are proven through Lyapunov analysis. The new nonlinear optimal control approach achieves fast and accurate tracking for all state variables of the brachiation robots, under moderate variations of the control inputs.

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TRBR: Flight body posture compensation for transverse ricochetal brachiation robot

Cited by 8 publications

References 12 publications

Design of Transverse Brachiation Robot and Motion Control System for Locomotion between Ledges at Different Elevations

Design of Transverse Brachiation Robot and Motion Control System for Locomotion between Ledges at Different Elevations

Multi-Locomotion Design and Implementation of Transverse Ledge Brachiation Robot Inspired by Sport Climbing

A Nonlinear Optimal Control Approach for Multi-DOF Brachiation Robots

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