Achieving Energy-Efficient Bipedal Walking Trajectory Through Ga-Based Optimization of Key Parameters

Dau, Van-Huan; Chew, Chee-Meng; Poo, A.N.

doi:10.1142/s0219843609001905

Cited by 24 publications

(11 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similarly, in the direction of motion, the modification should be such that prevent slippage of the landing foot on the new surface. By introducing the modification value in sagittal direction as: (10) And adding this modification value, as well as which guarantee smooth landing of the swing foot (Eq.7), the modified swing foot trajectory may be specified as: (11) In the case of advance landing of swing foot, by just modifying the swing foot trajectory, the adaptation is realized and no amendment is required for the pelvis trajectory. Hence, just the swing leg joints are modified to realize the adaptation (Figure 5.a).…”

Section: Advance Landing Of the Swing Footmentioning

confidence: 99%

Online adaptation for humanoids walking on uncertain surfaces

Khadiv

Moosavian

Yousefi‐Koma

et al. 2017

Proceedings of the Institution of Mechanical Engineers, Part I:

View full text Add to dashboard Cite

In this paper, an online adaptation algorithm for bipedal walking on uneven surfaces with height uncertainty is proposed. In order to generate walking patterns on flat terrains, the trajectories in the task space are planned to satisfy the dynamic balance and slippage avoidance constraints, and also to guarantee smooth landing of the swing foot. To ensure smooth landing of the swing foot on surfaces with height uncertainty, the preplanned trajectories in the task space should be adapted.The proposed adaptation algorithm consists of two stages. In the first stage, once the swing foot reaches its maximum height, the supervisory control is initiated until the touch is detected. After the detection, the trajectories in the task space are modified to guarantee smooth landing. In the second stage, this modification is preserved during the Double Support Phase (DSP), and released in the next Single Support Phase (SSP). Effectiveness of the proposed online adaptation algorithm is experimentally verified through realization of the walking patterns on the SURENA III humanoid robot, designed and fabricated at CAST. The walking is tested on a surface with various flat obstacles, where the swing foot is prone to either land on the ground soon or late.

show abstract

Section: Advance Landing Of the Swing Footmentioning

confidence: 99%

Online adaptation for humanoids walking on uncertain surfaces

Khadiv

Moosavian

Yousefi‐Koma

et al. 2017

Proceedings of the Institution of Mechanical Engineers, Part I:

View full text Add to dashboard Cite

show abstract

“…The criteria used in motion imitation other than motion similarity in terms of joint angles [16] include minimum consumed energy (MCE) [41,42,43], minimum torque change (MTC) [44], maximum motion velocity (MMV) [45] and minimum joint velocities (MJV) [46]. The advantages of MCE criterion are that the generated motion was relatively similar to that of human; and battery life or operation time is long.…”

Section: ) Similarity Between Human Motion and Robot Motionmentioning

confidence: 99%

Imitation of Dynamic Walking with BSN for a Humanoid Robot

Teachasrisaksakul

Zhang

Yang

et al. 2015

IEEE J. Biomed. Health Inform.

View full text Add to dashboard Cite

“…Many methods have been used to improve energy efficiency, such as compliant actuation design [2], [3], human walking learning [4], and gait parameters optimization [5], [6]. Generally, optimization-based approaches first evaluate a set of nominal step parameters and then update them following the gradient that minimizes the energetic cost of a desired travel distance.…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Bipedal Gait Pattern Generation via CoM Acceleration Optimization

Ding

Zhou

Xiao

2018

2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids)

View full text Add to dashboard Cite

Energy consumption for bipedal walking plays a central role for a humanoid robot with limited battery capacity. Studies have revealed that exploiting the allowable Zero Moment Point region (AZR) and Center of Mass (CoM) height variation (CoMHV) are strategies capable of improving energy performance. In general, energetic cost is evaluated by integrating the electric power of multi joints. However, this Joint-Power-based Index requires computing joint torques and velocities in advance, which usually requires time-consuming iterative procedures, especially for multi-joints robots. In this work, we propose a CoM-Acceleration-based Optimal Index (CAOI) to synthesize an energetically efficient CoM trajectory. The proposed method is based on the Linear Inverted Pendulum Model, whose energetic cost can be easily measured by the input energy required for driving the point mass to track a reference trajectory. We characterize the CoM motion for a single walking cycle and define its energetic cost as Unit Energy Consumption. Based on the CAOI, an analytic solution for CoM trajectory generation is provided. Hardware experiments demonstrated the computational efficiency of the proposed approach and the energetic benefits of exploiting AZR and CoMHV strategies.

show abstract

Achieving Energy-Efficient Bipedal Walking Trajectory Through Ga-Based Optimization of Key Parameters

Cited by 24 publications

References 8 publications

Online adaptation for humanoids walking on uncertain surfaces

Online adaptation for humanoids walking on uncertain surfaces

Imitation of Dynamic Walking with BSN for a Humanoid Robot

Energy-Efficient Bipedal Gait Pattern Generation via CoM Acceleration Optimization

Contact Info

Product

Resources

About