Adaptive Robot Biped Locomotion with Dynamic Motion Primitives and Coupled Phase Oscillators

The application of biped robots is always trapped by their high energy consumption. This paper makes a contribution by optimizing the joint torques to decrease the energy consumption without changing the biped gaits. In this work, a constrained quadratic programming (QP) problem for energy optimization is formulated. A neurodynamics-based solver is presented to solve the QP problem. Differing from the existing literatures, the proposed neurodynamics-based energy optimization (NEO) strategy minimizes the energy consumption and guarantees the following three important constraints simultaneously: (i) the force-moment equilibrium equation of biped robots, (ii) frictions applied by each leg on the ground to hold the biped robot without slippage and tipping over, and (iii) physical limits of the motors. Simulations demonstrate that the proposed strategy is effective for energyefficient biped walking.

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“…The main goal of this work is to minimize the expended energy given by (7). Then, the objective function can be presented as…”

Section: Assumptionmentioning

confidence: 99%

“…Biped robots receive a lot of attention from the scientists and engineers these years [1][2][3][4][5][6][7][8][9][10]. Compared with wheeled driven robots and crawler robots, biped robots have anthropomorphic adaptability to unstructured environments with relative less energy consumption.…”

Section: Introductionmentioning

confidence: 99%

Constrained Quadratic Programming and Neurodynamics-Based Solver for Energy Optimization of Biped Walking Robots

Wang

Chen

Jiang

et al. 2017

Mathematical Problems in Engineering

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“…Unlike in the abovementioned works, the DMPs used for this purpose must be learned in the task space; we call this approach the ''workspace DMP-based method''. This idea of using DMPs in the task space, which can be easily related to the task parameters, was first presented by Pastor et al [35] and Rosado et al [36] in the context of robot manipulation and bipedal walking. Subsequently, various task-space methods have been studied to improve the robustness and stability of bipedal motion by achieving objectives such as push recovery and disturbance resistance.…”

Section: Introductionmentioning

confidence: 99%

Workspace Trajectory Generation Method for Humanoid Adaptive Walking With Dynamic Motion Primitives

et al. 2020

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To properly function in real-world environments, a humanoid robot must be able to adapt its walking gait to new situations. In this paper, an adaptive bipedal walking control method that uses sensory feedback to modulate dynamic movement primitive (DMP) parameters is presented. This work addresses the challenge of adaptive locomotion by implementing DMPs in the workspace of a humanoid robot. This workspace formulation allows new movements to be created such that the DMP parameters, including the stride, height of the hip joint, foot clearance and forward velocity, are directly related to the walking pattern. One set of DMPs is applied to generate the foot trajectory, and a second set is used to generate the CoM (centre of mass) trajectory in an online fashion. Sensory feedback information is utilized to modify the generated CoM and foot trajectories to improve the walking quality. Furthermore, a staged evolutionary algorithm (EA) is designed to optimize the parameters of the control system to enhance the walking performance. The presented control strategy is demonstrated through simulations and real experiments that focus on the adaptation of the robot's walking pattern over sloped terrain. INDEX TERMS Humanoid robot, adaptive walking, dynamic movement primitives (DMPs), workspace trajectory generation.

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“…Dynamic movement primitive (DMP) framework is a biologically inspired trajectory generation method and has recently gained great attentions from the researchers (Ijspeert et al , 2013; Hoffmann et al , 2009; Ijspeert et al , 2002; Ijspeert et al , 2003; Basa and Schneider, 2015; Pastor et al , 2013; Park et al , 2008; Ude et al , 2010). The DMP framework is used in a wide array of applications including learning by demonstration (Tamosiunaite et al , 2011; Pignat and Calinon, 2017; Deniša et al , 2016; Kramberger et al , 2016; Abu-Dakka et al , 2014), mobile robots (Jiang et al , 2016), robot locomotion (Rosado et al , 2016), control applications (Krug and Dimitrov, 2015), human–robot and robot–robot cooperative tasks (Maeda et al , 2016; Kulvicius et al , 2013), exoskeletons (Kamali et al , 2016; Huang et al , 2016), humanoid robots (Mukovskiy et al , 2017; Li et al , 2014) and obstacle avoidance (Park et al , 2008; Ijspeert et al , 2013; Hoffmann et al , 2009; Tan et al , 2011; Hoffmann and Mitchell, 2016). The DMP method has a simple structure and low computation loads.…”

Section: Introductionmentioning

confidence: 99%

Real-time velocity scaling and obstacle avoidance for industrial robots using fuzzy dynamic movement primitives and virtual impedances

Kardan

Akbarzadeh

Mohammadi

2018

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Purpose This paper aims to increase the safety of the robots’ operation by developing a novel method for real-time implementation of velocity scaling and obstacle avoidance as the two widely accepted safety increasing concepts. Design/methodology/approach A fuzzy version of dynamic movement primitive (DMP) framework is proposed as a real-time trajectory generator with imbedded velocity scaling capability. Time constant of the DMP system is determined by a fuzzy system which makes decisions based on the distance from obstacle to the robot’s workspace and its velocity projection toward the workspace. Moreover, a combination of the DMP framework with a human-like steering mechanism and a novel configuration of virtual impedances is proposed for real-time obstacle avoidance. Findings The results confirm the effectiveness of the proposed method in real-time implementation of the velocity scaling and obstacle avoidance concepts in different cases of single and multiple stationary obstacles as well as moving obstacles. Practical implications As the provided experiments indicate, the proposed method can effectively increase the real-time safety of the robots’ operations. This is achieved by developing a simple method with low computational loads. Originality/value This paper proposes a novel method for real-time implementation of velocity scaling and obstacle avoidance concepts. This method eliminates the need for modification of original DMP formulation. The velocity scaling concept is implemented by using a fuzzy system to adjust the DMP’s time constant. Furthermore, the novel impedance configuration makes it possible to obtain a non-oscillatory convergence to the desired path, in all degrees of freedom.

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Adaptive Robot Biped Locomotion with Dynamic Motion Primitives and Coupled Phase Oscillators

Cited by 8 publications

References 39 publications

Constrained Quadratic Programming and Neurodynamics-Based Solver for Energy Optimization of Biped Walking Robots

Constrained Quadratic Programming and Neurodynamics-Based Solver for Energy Optimization of Biped Walking Robots

Workspace Trajectory Generation Method for Humanoid Adaptive Walking With Dynamic Motion Primitives

Real-time velocity scaling and obstacle avoidance for industrial robots using fuzzy dynamic movement primitives and virtual impedances

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