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Path Planning and Sensing for Autonomous Control of Robot Manipulators

10th Annual COE Graduate Poster Presentation Competition

Student: Amanuel Abrdo Tereda (PhD)

Advisor: Dr. Sun Yi

Cross-Disciplinary Research Area: Robotics

Automating and optimizing the process of Pick-and-place automation with various path planning techniques contributes to the expansion of application areas. This research offers a nonlinear model predictive control (NLMPC) path planning approach for the KINOVA Gen3 multifunctional robotic manipulator, which was newly developed and has seven degrees of freedom. In the presence of input constraints, the paper also manages to monitor reference trajectories in order to achieve the goal of identifying and arranging distinct objects.

Fig 2. Overall simulation world, a blue broken line which indicates the path followed by the robot which is created by NLMPC and objects at their initial position.

Fig 1. Chart which dictates how the manipulator interacts with the objects and parts.

Fig 3. Automation of the manipulator while sorting objects by their color and avoiding obstacles.

Fig 4. Application of the research on lab existing KINOVA Gen2 robot.

The research's goal of creating a controller for planning and control based on NLMPC, as well as building elements of a 3D simulation environment to show the control technique for robot arms, has been accomplished successfully. However, there are some tasks that must be considered in the future:

• Replacing the object detection mechanisms with sensor measurements such as camera pictures or point clouds from 3D scanner and a Lidar camera.
• A ground robot can be employed to move the robotic arm a more considerable distance after picking the desired object.

Abstract

Methodology

Implementation and Result

Application

Conclusion and Future work