Related papers: A Vision-Based Collision Sensing Method for Stable…
Modern humanoid robots have shown their promising potential for executing various tasks involving the grasping and manipulation of objects using their end-effectors. Nevertheless, in the most of the cases, the grasping and manipulation…
We propose a novel tri-fingered soft robotic gripper with decoupled stiffness and shape control capability for performing adaptive grasping with minimum system complexity. The proposed soft fingers adaptively conform to object shapes…
In industrial applications, complex tasks require human collaboration since the robot doesn't have enough dexterity. However, the robots are still implemented as tools and not as collaborative intelligent systems. To ensure safety in the…
How should a robot direct active vision so as to ensure reliable grasping? We answer this question for the case of dexterous grasping of unfamiliar objects. By dexterous grasping we simply mean grasping by any hand with more than two…
Soft robotic grippers are shown to be high effective for grasping unstructured objects with simple sensing and control strategies. However, they are still limited by their speed, sensing capabilities and actuation mechanism. Hence, their…
Collision detection is a core component of robotics applications such as simulation, control, and planning. Traditional algorithms like GJK+EPA compute witness points (i.e., the closest or deepest-penetration pairs between two objects) but…
Grasping deformable objects with varying stiffness remains a significant challenge in robotics. Estimating the local stiffness of a target object is important for determining an optimal grasp pose that enables stable pickup without damaging…
We describe a learning-based approach to hand-eye coordination for robotic grasping from monocular images. To learn hand-eye coordination for grasping, we trained a large convolutional neural network to predict the probability that…
Grasping a variety of objects remains a key challenge in the development of versatile robotic systems. The human hand is remarkably dexterous, capable of grasping and manipulating objects with diverse shapes, mechanical properties, and…
In essence, successful grasp boils down to correct responses to multiple contact events between fingertips and objects. In most scenarios, tactile sensing is adequate to distinguish contact events. Due to the nature of high dimensionality…
Sensory feedback is essential for the control of soft robotic systems and to enable deployment in a variety of different tasks. Proprioception refers to sensing the robot's own state and is of crucial importance in order to deploy soft…
Recently, suction-based robotic systems with microscopic features or active suction components have been proposed to grip rough and irregular surfaces. However, sophisticated fabrication methods or complex control systems are required for…
Tactile sensing represents a crucial technique that can enhance the performance of robotic manipulators in various tasks. This work presents a novel bioinspired neuromorphic vision-based tactile sensor that uses an event-based camera to…
The presence of post-stroke grasping deficiencies highlights the critical need for the development and implementation of advanced compensatory strategies. This paper introduces a novel system to aid chronic stroke survivors through the…
Aerial manipulation requires force-aware capabilities to enable safe and effective grasping and physical interaction. Previous works often rely on heavy, expensive force sensors unsuitable for typical quadrotor platforms, or perform…
The objective of this paper is to describe an approach to detect the slip and contact force in real-time feedback. In this novel approach, the DAVIS camera is used as a vision tactile sensor due to its fast process speed and high…
Soft and lightweight grippers have greatly enhanced the performance of robotic manipulators in handling complex objects with varying shape, texture, and stiffness. However, the combination of universal grasping with passive sensing…
Robotic vision plays a key role for perceiving the environment in grasping applications. However, the conventional framed-based robotic vision, suffering from motion blur and low sampling rate, may not meet the automation needs of evolving…
A key challenge in robotics is to create efficient methods for grasping objects with diverse shapes, sizes, poses, and properties. Grasping with hand-like end effectors often requires careful selection of hand orientation and finger…
Soft grippers, for stable grasping of objects, with high compliance could be considered a suitable candidate for replacement of conventional rigid grippers, and in recent years, they have been emerging exponentially in industries. Not only…