Gabriel Bermudez

Mr. Gabriel Bermudez

orcid

Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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13 June 2024 in Sensors
Verified
Journal Article
Open access
PDF file
GPGabriel Duarte Gonçalves Pedro
Gabriel Duarte Gonçalves Pedro
GBGabriel Bermudez
Gabriel Bermudez
VMVivian Suzano Medeiros
Vivian Suzano Medeiros
HNHélio Jacinto da Cruz Neto
Hélio Jacinto da Cruz Neto
LBLuiz Guilherme Dias de Barros
Luiz Guilherme Dias de Barros
TBThiago Boaventura
Thiago Boaventura
In robotics, the ability of quadruped robots to perform tasks in industrial, mining, and disaster environments has already been demonstrated. To ensure the safe execution of tasks by the robot, meticulous planning of its foot placements and precise leg control are crucial. Traditional motion planning and control methods for quadruped robots often rely on complex models of both the robot itself and its surrounding environment. Establishing these models can be challenging due to their nonlinear nature, often entailing significant computational resources. However, a more simplified approach exists that focuses on the kinematic model of the robot’s floating base for motion planning. This streamlined method is easier to implement but also adaptable to simpler hardware configurations. Moreover, integrating impedance control into the leg movements proves advantageous, particularly when traversing uneven terrain. This article presents a novel approach in which a quadruped robot employs impedance control for each leg. It utilizes sixth-degree Bézier curves to generate reference trajectories derived from leg velocities within a planar kinematic model for body control. This scheme effectively guides the robot along predefined paths. The proposed control strategy is implemented using the Robot Operating System (ROS) and is validated through simulations and physical experiments on the Go1 robot. The results of these tests demonstrate the effectiveness of the control strategy, enabling the robot to track reference trajectories while showing stable walking and trotting gaits.