Automatic Onsite Grinding of Large Complex Surfaces

Description of the image

Polishing and grinding of metallic parts is an important manufacturing operation in many industrial applications. It remains challenging to polish large complex surfaces. Polishing is predominantly done manually which is very time consuming, expensive and more importantly, can be a safety hazard for human operators using hand-held devices. We propose the assembly of a robot capable of polishing complex and relatively large surface areas of complex free form fabricated parts. By developing this robot for a complex and potentially un-safe operation, this application will lower the technical, operational, and economic barriers for companies to adopt robotic technologies.

Sponsor: Advanced Robotics for Manufacturing Institute

Period of Performance: 2019 ~ 2024

Point of Contact: Weiye Zhao

Publications:

[C30] Contact-Rich Trajectory Generation in Confined Environments Using Iterative Convex Optimization
Wei-Ye Zhao, Suqin He, Chengtao Wen and Changliu Liu
Dynamic Systems and Control Conference, 2020
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Abstract:

Applying intelligent robot arms in dynamic uncertain environments (i.e., flexible production lines) remains challenging, which requires efficient algorithms for real time trajectory generation. The motion planning problem for robot trajectory generation is highly nonlinear and nonconvex, which usually comes with collision avoidance constraints, robot kinematics and dynamics constraints, and task constraints (e.g., following a Cartesian trajectory defined on a surface and maintain the contact). The nonlinear and nonconvex planning problem is computationally expensive to solve, which limits the application of robot arms in the real world. In this paper, for redundant robot arm planning problems with complex constraints, we present a motion planning method using iterative convex optimization that can efficiently handle the constraints and generate optimal trajectories in real time. The proposed planner guarantees the satisfaction of the contact-rich task constraints and avoids collision in confined environments. Extensive experiments on trajectory generation for weld grinding are performed to demonstrate the effectiveness of the proposed method and its applicability in advanced robotic manufacturing.

Video:

[C69] Hybrid Task Constrained Incremental Planner for Robot Manipulators in Confined Environments
Yifan Sun, Weiye Zhao and Changliu Liu
American Control Conference, 2024
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