Robotics

We present an interactive design system that allows users to create sculpting styles and fabricate clay models using a standard 6-axisrobot arm.

We present a computational technique that aids with the design of structurally-sound metal frames, tailored for robotic fabrication using an existing process that integrate automated bar bending, welding, and cutting. Aligning frames with structurally-favorable orientations, and decomposing models into fabricable units, we make the fabrication process scale-invariant, and frames globally align in an aesthetically-pleasing and structurally-informed manner.

This paper describes the development of a system for lifelike gaze in human-robot interactions using a humanoid animatronic bust. We present a general architecture that seeks not only to create gaze interactions from a technological standpoint, but also through the lens of character animation where the fidelity and believability of motion is paramount; that is, we seek to create an interaction which demonstrates the illusion of life.

In this paper we investigate the role of haptic feedback in human/robot handshaking by comparing different force controllers. The basic hypothesis is that in human handshaking force control there is a balance between an intrinsic (open--loop) and extrinsic (closed--loop) contribution. We use an underactuated anthropomorphic robotic hand, the Pisa/IIT hand, instrumented with a set of pressure sensors estimating the grip force applied by humans. In a first set of experiments we ask subjects to mimic a given force profile applied by the robot hand, to understand how human perceive and are able to reproduce a handshaking force.

This paper presents a system for soft human-robot handshaking, using a soft robot hand in conjunction witha lightweight and impedance-controlled robot arm. Using this system, we study how different factors influencethe perceived naturalness, and give the robot different personality traits. Capitalizing on recent findings regardinghandshake grasp force regulation, and on studies of the impedance control of the human arm, we investigate the roleof arm stiffness as well as the kinaesthetic synchronization of human and robot arm motions during the handshake.The system is implemented using a lightweight anthropomorphic arm, with a Pisa/IIT Softhand wearing a sensorizedsilicone glove as the end-effector.

Soft robots have applications in safe human-robot interactions, manipulation of fragile objects, and locomotion in challenging and unstructured environments. In this paper, we present a computational method for augmenting soft robots with proprioceptive sensing capabilities. Our method automatically computes a minimal stretch-receptive sensor network to user-provided soft robotic designs, which is optimized to perform well under a set of user-specified deformation-force pairs. The sensorized robots are able to reconstruct their full deformation state, under interaction forces. We cast our sensor design as a sub-selection problem, selecting a minimal set of sensors from a large set of fabricable ones which minimizes the error when sensing specified deformation-force pairs. Unique to our approach is the use of an analytical gradient of our reconstruction performance measure with respect to selection variables. We demonstrate our technique on a bending bar and gripper example, illustrating more complex designs with a simulated tentacle.

We propose a novel generic shape optimization method for CAD models based on the eXtended Finite Element Method (XFEM).

We present a system for fast and robust handovers with a robot character, together with a user study investigating the effect of robot speed and reaction time on perceived interaction quality. The system can match and exceed human speeds and confirms that users prefer human-level timing.

Creating animations for robotic characters is very challenging due to the constraints imposed by their physical nature. In particular, the combination of fast motions and unavoidable structural deformations leads to mechanical oscillations that negatively affect their performances. Our goal is to automatically transfer motions created using traditional animation software to robotic characters while avoiding such artifacts.