Component based computational model for bipedal locomotion

Chakraborty, Rupak; Nandi, Gora Chand; Kundu, Soumya

doi:10.1016/j.robot.2016.03.005

Cited by 1 publication

(1 citation statement)

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“…In doing so, the entire gait cycle has been discretized into phases and subphases and modeled using a hybrid automaton, subsequently the automaton has been integrated with the BIP (Behavior, Interaction, and Priority) framework, thereby creating a component based computational framework for modeling biped locomotion. The correctness of the developed model has been validated and verified through simulation runs in open sim [10]. The conventional models of bipedal walking generally assume rigid body structures, while elastic material properties seem to play an essential role in nature.…”

Section: Introductionmentioning

confidence: 96%

Optimal Design of Biped Amble Mechanism using Matlab

Bammidi¹,

Raghuveer²,

Dowluru³

et al. 2021

Int J Robot Eng

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From past decades, the different types of mechanisms in mobile robots have been created so far which includes legged, treaded-tyre and wheeled type robots. Among these types, the wheeled type is easiest to control while the treaded-tyre type offers improved flexibility. Legged locomotion, though not widely used for industrial purposes, has growing implications mainly due to its ease of maneuvering in rough terrains. The Walking motion is obtained through various mechanisms. It is the crank and rocker mechanism, which gives a walking style characteristic of human being. The present research work uses a different type of mechanism for driving a biped that is most distinguished by its ease of operation that produces a type of 'walk' similar to two legged mammals. In this research initially, a multi-objective optimization is carried out for the optimal design of the mechanism. This research involves a simulation of a simple Biped model using Crank-Rocker mechanism. The design of the biped robot is done by considering two important objective parameters stride and lift, a multi objective function must be created and optimization is done by using MATLAB Programming.

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Section: Introductionmentioning

confidence: 96%