Is this project an undergraduate, graduate, or faculty project?
Undergraduate
Project Type
individual
Campus
Daytona Beach
Authors' Class Standing
Jasmine Nakladov, Senior
Lead Presenter's Name
Jasmine Nakladov
Lead Presenter's College
DB College of Engineering
Faculty Mentor Name
Cagri Kilic
Abstract
As robots become increasingly capable of navigating difficult terrains, their ability to perform tasks requiring precise manipulation while maintaining mobility has continued to be an area of interest. One of the most common configurations of such robots is the combination of a quadrupedal base with a mounted manipulator arm that can perform complex tasks. However, stable manipulation becomes a challenge with this configuration due to disturbances introduced by the robot’s gait. Inspired by “chicken-head” stabilization, this project aims to investigate the effectiveness of Model Predictive Control (MPC) in maintaining a stable end-effector of a robotic arm mounted on a quadruped robot. To achieve this goal, a ROS2 simulation environment utilizing Gazebo and MoveIt 2 is developed, with MPC optimization implemented through CasADi to compute joint trajectories in real-time. The simulation introduces disturbances through deliberate base movements representing different gait patterns. Simulation results show that the MPC controller successfully maintains end-effector stability despite the perturbations, highlighting MPC’s ability to employ precise and stable manipulation of a quadruped-robotic arm combination. Following the simulation, the control system is implemented and validated on the physical models to assess real-world performance. Accomplishment of this idea will allow for further applications in end-effector stabilization, being particularly effective in planetary exploration missions and allowing robots to perform tasks aiding in their traversal, sample collection, and more
Did this research project receive funding support (Spark, SURF, Research Abroad, Student Internal Grants, Collaborative, Climbing, or Ignite Grants) from the Office of Undergraduate Research?
Yes, Spark Grant
End-Effector Stabilization of a Robotic Arm using Model Predictive Control
As robots become increasingly capable of navigating difficult terrains, their ability to perform tasks requiring precise manipulation while maintaining mobility has continued to be an area of interest. One of the most common configurations of such robots is the combination of a quadrupedal base with a mounted manipulator arm that can perform complex tasks. However, stable manipulation becomes a challenge with this configuration due to disturbances introduced by the robot’s gait. Inspired by “chicken-head” stabilization, this project aims to investigate the effectiveness of Model Predictive Control (MPC) in maintaining a stable end-effector of a robotic arm mounted on a quadruped robot. To achieve this goal, a ROS2 simulation environment utilizing Gazebo and MoveIt 2 is developed, with MPC optimization implemented through CasADi to compute joint trajectories in real-time. The simulation introduces disturbances through deliberate base movements representing different gait patterns. Simulation results show that the MPC controller successfully maintains end-effector stability despite the perturbations, highlighting MPC’s ability to employ precise and stable manipulation of a quadruped-robotic arm combination. Following the simulation, the control system is implemented and validated on the physical models to assess real-world performance. Accomplishment of this idea will allow for further applications in end-effector stabilization, being particularly effective in planetary exploration missions and allowing robots to perform tasks aiding in their traversal, sample collection, and more