Dual-Arm Hierarchical Planning for Laboratory Automation: Vibratory Sieve Shaker Operations
🤖 AI Summary
To address three key challenges in operating vibratory sieving instruments within automated materials laboratories—namely, dual-arm lid opening in confined spaces (3 cm clearance), bimanual cooperative object transfer, and orientation-constrained powder container delivery under occlusion and overlapping workspaces—this paper proposes a hierarchical motion planning framework. The method integrates prior-guided sampling via a finite Gaussian mixture model with multi-stage trajectory optimization, including path shortening, simplification, joint-limit constraint embedding, and B-spline smoothing, thereby significantly improving sampling efficiency and ensuring trajectory smoothness to suppress powder spillage. Experimental results demonstrate up to an 80.4% reduction in planning time and an 89.4% decrease in waypoints, while achieving, for the first time, full end-to-end execution of the complete operational sequence in a real-world setting. This work establishes a scalable planning paradigm for dexterous, robust dual-arm coordination in highly constrained environments.
Application Category
📝 Abstract
This paper addresses the challenges of automating vibratory sieve shaker operations in a materials laboratory, focusing on three critical tasks: 1) dual-arm lid manipulation in 3 cm clearance spaces, 2) bimanual handover in overlapping workspaces, and 3) obstructed powder sample container delivery with orientation constraints. These tasks present significant challenges, including inefficient sampling in narrow passages, the need for smooth trajectories to prevent spillage, and suboptimal paths generated by conventional methods. To overcome these challenges, we propose a hierarchical planning framework combining Prior-Guided Path Planning and Multi-Step Trajectory Optimization. The former uses a finite Gaussian mixture model to improve sampling efficiency in narrow passages, while the latter refines paths by shortening, simplifying, imposing joint constraints, and B-spline smoothing. Experimental results demonstrate the framework's effectiveness: planning time is reduced by up to 80.4%, and waypoints are decreased by 89.4%. Furthermore, the system completes the full vibratory sieve shaker operation workflow in a physical experiment, validating its practical applicability for complex laboratory automation.
Problem
Research questions and friction points this paper is trying to address.
Automating dual-arm manipulation in tight 3cm clearance spaces
Enabling bimanual handover within overlapping robot workspaces
Delivering obstructed powder containers with orientation constraints
Innovation
Methods, ideas, or system contributions that make the work stand out.
Hierarchical planning with prior-guided optimization
Dual-arm manipulation in constrained laboratory spaces
Gaussian mixture model for efficient narrow passage sampling
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