This paper presents robotic manipulation methods for rapid high-arc object transfer using dynamic, non-prehensile interactions. Two complementary techniques are introduced, two-fingered scoop-and-flick and one-fingered topple-and-flick, designed for objects with low and high centers of mass, respectively. Both methods enable a robot to retrieve objects resting on a surface and launch them into controlled projectile trajectories without requiring stable grasp formation. To support these maneuvers, we develop physics-based models of object acquisition and release, and combine them with a data-driven framework. While analytical modeling guides the acquisition phase, the highly nonlinear flicking dynamics are captured using learned predictive models that enable accurate selection of control parameters for desired trajectories. The proposed techniques enable dynamic object transfer, reduced grasp planning complexity, and adaptability to environmental constraints. Experiments conducted on a custom robotic platform demonstrate reliable and accurate high-arc object transfer, in which the majority of object displacement is achieved through projectile motion.

This paper presents tilt-and-pivot manipulation, a robotic technique for picking large, thin objects resting on hard supporting surfaces. The method employs in-hand dexterous manipulation by reorienting the gripper around the object’s contact point, allowing a finger to enter the gap between the object and the surface, without requiring relative sliding at the contact. This finally facilitates reliable pinch grasps on the object’s faces. We investigate the kinematic principles and planning strategies underlying tilt-and-pivot, discuss effector design considerations, and highlight the practical advantages of the strategy, which is applicable to a variety of low-profile objects. Experimental results, incorporating vision and force–torque sensing, demonstrate its effectiveness in bin-picking scenarios and its applicability to more complex object-handling tasks.

This work examines the robotic technique of ungrasping, in which an object held by a gripper is intentionally released into the environment. The proposed method achieves controlled object release through non-static contact interactions that permit rolling and sliding. This form of dexterous manipulation is especially important for thin or slender objects, as demonstrated through physical experiments. This study first addresses how three-dimensional stability can be established using a minimal number of contacts. It then introduces a planning framework for three-dimensional ungrasping that extends our prior planar formulation. Experimental results obtained with a two-fingered gripper—the most common gripper type—validate the feasibility, effectiveness, and practicality of the presented approach.

This paper investigates robotic surface-to-surface object transfer, a release manipulation task in which a robot transfers an object from an end-effector that functions solely as a large supporting surface to an external surface such as the ground. Such transfers commonly arise in many practical manipulation scenarios. Unlike simple releasing actions, surface-to-surface transfer requires maintaining force equilibrium through controlled rolling and sliding at the contact interfaces. We present a manipulation model that captures the essential contact kinematics and enables force balance throughout the transfer. To assess robustness, we introduce a stability simulation framework that evaluates dynamic stability by monitoring variations in gravitational potential energy across object configurations. The proposed approach is implemented on a quadrupedal robot and validated through a series of experiments with objects of varying geometries. The results demonstrate the effectiveness of the method and underscore the role of stability-aware control in surface-to-surface transfer.