Optimal trajectory generation for a prismatic joint biped robot using genetic algorithms

Capi, Genci; Kaneko, Shin-ichiro; Mitobe, Kazuhisa; Barolli, Leonard; Nasu, Yasuo

doi:10.1016/s0921-8890(01)00177-4

Cited by 56 publications

(37 citation statements)

References 7 publications

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“…In (Verrelst et al, 2004), the authors designed a biped walking mechanism actuated using pneumatic muscles. Capi (2002) introduced an optimal scheme for a biped robot that has two legs with two DOF each. One translational DOF achieved by a DC motor attached at the body of the robot, and the other DOF is the rotational motion at the ankle joint.…”

Section: Introductionmentioning

confidence: 99%

Biomimetic Design of a Single DOF Stephenson III Leg Mechanism

Batayneh¹,

Al-Araidah²,

Malkawi³

2013

MER

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The article presents a single degree-of-freedom (DOF) Stephenson III mechanical reproduction of the shape and movement of the human leg. Type and motion synthesis of the mechanism are achieved through qualitative and interactive design heuristics. Qualitative considerations include the slim straight shape of the human leg to help keeping the center of mass of the body far from ground. Moreover, the driving force and controllers of the walking apparatus are located within the upper part of the leg. We utilize Working Model software package to test and tune the segments of the mechanism to arrive at the desired walking gait. The resulting mechanism is a reproduction of the human walking apparatus with minimum control.

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Section: Introductionmentioning

confidence: 99%

Biomimetic Design of a Single DOF Stephenson III Leg Mechanism

Batayneh¹,

Al-Araidah²,

Malkawi³

2013

MER

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“…However, the timing of foot contact with the ground and lift-off was predetermined and constant, and the phase difference between the front and rear feet remained constant regardless of the galloping state. In time, robot trajectories were modeled as polynomials and the robot state was parameterized with a polynomial function, which was used for optimization by a genetic algorithm [12]. Among the many optimization algorithms, genetic algorithms are the best for finding global solutions in highly nonlinear systems [13,14].…”

Section: Introductionmentioning

confidence: 99%

Trajectory optimization with GA and control for quadruped robots

Chae

Park

2009

J Mech Sci Technol

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This paper proposes an optimal galloping trajectory, which costs low energy and guarantees the stability of the quadruped robot. In the realization of fast galloping, the trajectory design is important. For a galloping trajectory, we propose an elliptic leg trajectory, which provides simplified locomotion to complex galloping motions of animals. However, the elliptic trajectory, as an imitation of animal galloping motion, does not guarantee stability and minimal energy consumption. We propose optimization based on energy and stability using a genetic algorithm, which provides a robust and globally optimized solution to this multi-body, highly nonlinear dynamic system. To evaluate and verify the effectiveness of the proposed trajectory, a series of computer simulations were carried out.

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“…Westervelt and Grizzle used an optimization package called DIRCOL, which implements an SQP algorithm and a variable number of cubic splines to approximate the state (8) . Capi et al parameterized a robot state as a polynomial function and used a genetic algorithm for the optimization (9) . Silva et al searched for the optimal step length, hip height, link lengths and link masses, and so on, to minimize the energy consumption (10) .…”

Section: Introductionmentioning

confidence: 99%

“…Genetic algorithms are known to be efficient and robust in searching for a global solution in optimization (9), (12) - (14) . The real-coded genetic algorithm is used due to its simplicity, speed, and easiness to deal with complex constraints.…”

Section: Introductionmentioning

confidence: 99%

Generation of an Optimal Gait Trajectory for Biped Robots Using a Genetic Algorithm

Park

Choi

2004

JSME Int. J., Ser. C

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This paper proposes a method that minimizes the energy consumption in the locomotion of a biped robot. A real-coded genetic algorithm is employed in order to search for the optimal locomotion pattern, and at the same time the optimal locations of the mass centers of the links that compose the biped robot. Since many of the essential characteristics of the human walking motion can be captured with a seven-link planar biped walking in the saggital plane, a 6-DOF biped robot that consists of seven links is used as the model used in the work. For trajectories of the robot in a single stride, fourth-order polynomials are used as their basis functions to approximate the locomotion gait. The coefficients of the polynomials are defined as design variables. For the optimal locations of the mass centers of the links, three variables are added to the design variables under the assumption that the left and right legs are identical. Simulations were performed to compare locomotion trajectories obtained with the genetic algorithm and the one obtained with the gravity-compensated inverted pendulum mode (GCIPM). They show that the proposed trajectory with the optimized mass centers significantly reduces the energy consumption, indicating that the proposed optimized method is a valuable tool in the design of biped robots.

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Optimal trajectory generation for a prismatic joint biped robot using genetic algorithms

Cited by 56 publications

References 7 publications

Biomimetic Design of a Single DOF Stephenson III Leg Mechanism

Biomimetic Design of a Single DOF Stephenson III Leg Mechanism

Trajectory optimization with GA and control for quadruped robots

Generation of an Optimal Gait Trajectory for Biped Robots Using a Genetic Algorithm

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