17 accepted papers
One of the primary reasons robotic apple harvesting is a challenging manipulation problem is the cluttered tree canopy. An effective harvesting gripper should i) be compact to minimize collisions with the canopy, ii) offer a compliant grasp to prevent bruising; and iii) hold the fruit securely to co…
Dormant tree pruning is laborintensive but essential to maintaining modern highly-productive fruit orchards. In this work we present a closed-loop visuomotor controller for robotic pruning. The controller guides the cutter through a cluttered tree environment to reach a specified cut point and ensur
We present and evaluate a novel suction-based gripper designed for fruit picking. This work is motivated by common problems observed in field trials of robotic harvesting: Calibration/perception errors, workspace obstacles, fruit swinging/moving when contacted, and varying stem and branch stiffnesse…
Advancing robotic grasping and manipulation requires the ability to test algorithms and/or train learning models on large numbers of grasps. Towards the goal of more advanced grasping, we present the Grasp Reset Mechanism (GRM), a fully automated apparatus for conducting large-scale grasping trials.…
Robotic in-hand manipulation increases the capability of robotic hands to interact with the world. The amount of manipulation that a robot is capable of is highly dependent on the design of the robot hand, and previous works have shown success in designing hands to improve performance for different…
This letter presents a novel benchmark called the Asterisk Test that characterizes a hand’s ability to translate an object on a table in eight linear directions using only two fingers. The benchmark is agnostic to the controller, object, and robot hand used. The benchmark also enables a measure of t
In this paper we investigate the influence interfaces and feedback have on human-robot trust levels when operating in a shared physical space. The task we use is specifying a “no-go” region for a robot in an indoor environment. We evaluate three styles of interface (physical, AR, and map-based) and…
Machine vision is a critical subsystem for enabling robots to be able to perform a variety of tasks in orchard environments. However, orchards are highly visually complex environments, and computer vision algorithms operating in them must be able to contend with variable lighting conditions and back…
Robotic tree pruning requires highly precise manipulator control in order to accurately align a cutting implement with the desired pruning point at the correct angle. Simultaneously, the robot must avoid applying excessive force to rigid parts of the environment such as trees, support posts, and wir…
Apple picking is a challenging manipulation task, but it is difficult to test solutions due to the limited window of time that apples are in season. Previous methods have built simulations of apple trees, but simulations rarely capture soft contact and deformation well, both of which are common in f…
We present a method for classifying the quality of near-contact grasps using spatial metrics that are recoverable from sensor data. Current methods often rely on calculating precise contact points, which are difficult to calculate in real life, or on tactile sensors or image data, which may be unava…
Numerous grasp planning algorithms have been proposed since the 1980s. The grasping literature has expanded rapidly in recent years, building on greatly improved vision systems and computing power. Methods have been proposed to plan stable grasps on known objects (exact 3D model is available), famil
Grasping a simple object from the side is easy — unless the object is almost as big as the hand or space constraints require positioning the robot hand awkwardly with respect to the object. We show that humans — when faced with this challenge — adopt coordinated finger movements which enable them to…
In this paper we define two feature representations for grasping. These representations capture hand-object geometric relationships at the near-contact stage - before the fingers close around the object. Their benefits are: 1) They are stable under noise in both joint and pose variation. 2) They are…
This paper presents an online data collection method that captures human intuition about what grasp types are preferred for different fundamental object shapes and sizes. Survey questions are based on an adopted taxonomy that combines grasp pre-shape, approach, wrist orientation, object shape, orien…
We present a human-subjects study approach that supports the analysis of the manipulation performance of robotic hands that have the same morphology but different actuation and compliance. Specifically, we use this approach to analyze three different types of hands (one underactuated, one fully actu…
We analyze visual cues people used to evaluate a robot grasp. Participants were presented with two (front and side) orthogonal views of a robot hand grasping an object and asked how successful the grasp would be on a scale of 1-5; they were eye-tracked while completing this survey. Ground truth of t