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Most successes in autonomous robotic assembly have been restricted to single target or category. We propose to investigate general part assembly, the task of creating novel target assemblies with unseen part shapes. As a fundamental step to a general part assembly system, we tackle the task of determining the precise poses of the parts in the target assembly, which we term “rearrangement planning". We present General Part Assembly Transformer (GPAT), a transformer-based model architecture that accurately predicts part poses by inferring how each part shape corresponds to the target shape. Our experiments on both 3D CAD models and real-world scans demonstrate GPAT’s generalization abilities to novel and diverse target and part shapes. 

We present a prototype virtual reality user interface for robot teleoperation that supports high-level specification of 3D object positions and orientations in remote assembly tasks. Users interact with virtual replicas of task objects. They asynchronously assign multiple goals in the form of 6DoF destination poses without needing to be familiar with specific robots and their capabilities, and manage and monitor the execution of these goals. The user interface employs two different spatiotemporal visualizations for assigned goals: one represents all goals within the user’s workspace (Aggregated View), while the other depicts each goal within a separate world in miniature (Timeline View). We conducted a user study of the interface without the robot system to compare how these visualizations affect user efficiency and task load. The results show that while the Aggregated View helped the participants finish the task faster, the participants preferred the Timeline View.