Time-Optimized Trajectory Planning for Non-Prehensile Object Transportation in 3D

TL;DR

This paper tackles the slow and unstable nature of non-prehensile object transport by introducing a stability-aware trajectory planning framework that explicitly integrates tray rotation. A physical model with a fixed object–tray joint and a 6D contact formulation captures tipping and force interactions, yielding a bound on translational acceleration that depends on tray rotation, geometry, and inertial effects. The authors propose a two-stage planner: first generate a rotational trajectory for the tray via an S-curve, then compute the translational motion from a derived equation, all under unified jerk, acceleration, and velocity constraints. Experimental validation on a 7-DoF Panda demonstrates substantial time savings (theoretically up to $25\%$ and experimentally up to $47.2\%$) when leveraging tray rotation, indicating notable practical gains for fast, stable non-prehensile transportation in 3D.

Abstract

Non-prehensile object transportation offers a way to enhance robotic performance in object manipulation tasks, especially with unstable objects. Effective trajectory planning requires simultaneous consideration of robot motion constraints and object stability. Here, we introduce a physical model for object stability and propose a novel trajectory planning approach for non-prehensile transportation along arbitrary straight lines in 3D space. Validation with a 7-DoF Franka Panda robot confirms improved transportation speed via tray rotation integration while ensuring object stability and robot motion constraints.

Figures (3)

• Figure 1: Illustration of object and tray motion.
• Figure 2: Physical model and trajectory illustration.
• Figure 3: Experiment results.