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Designing Cable Driven Actuation Networks for Kinematic Chains and Trees

In this paper we present an optimization-based approach for the design of cable-driven kinematic chains and trees. Our system takes as input a hierarchical assembly consisting of rigid links jointed together with hinges. The user also specifies a set of target poses or keyframes using inverse kinematics. Our approach places torsional springs at the joints and computes a cable network that allows us to reproduce the specified target poses. We start with a large set of cables that have randomly chosen routing points and we gradually remove the redundancy. Then we refine the routing points taking into account the path…

Snapbot: A Reconfigurable Legged Robot

We develop a reconfigurable legged robot, named Snapbot, to emulate configuration changes and various styles of legged locomotion. The body of Snapbot houses a microcontroller and a battery for untethered operation. The body also contains connections for communication and power to the modular legs. The legs can be attached to and detached from the body using magnetic mechanical couplings. In the center of this coupling, there is a multi-pin spring-loaded electrical connector that distributes power and transmits data between the controller and leg actuators. The locomotion algorithm is implemented on the microcontroller. The algorithm enables Snapbot to locomote in various…

MetaSilicone: Design and Fabrication of Composite Silicone with Desired Mechanical Properties

We present a method for designing and fabricating MetaSilicones—composite silicone rubbers that exhibit desired macroscopic mechanical properties. The underlying principle of our approach is to inject spherical inclusions of a liquid dopant material into a silicone matrix material. By varying the number, size, and locations of these inclusions as well as their material, a broad range of mechanical properties can be achieved. The technical core of our approach is formed by an optimization algorithm that, combining a simulation model based on extended finite elements (XFEM) and sensitivity analysis, computes inclusion distributions that lead to desired stiffness properties on the macroscopic…

Interacting Intelligent Characters AR

In this paper, we explore interacting with virtual characters in AR along real-world environments. Our vision is that virtual characters will be able to understand the real-world environment and interact in an intelligent and realistic manner with it. For example, a character can walk around un-even stairs and slopes, or be pushed away by collisions with real-world objects like a ball. We describe how to automatically animate a new character, and imbue it’s motion with adaption to environments and reactions to perturbations from the real world.  

Enabling Interactive Infrastructure with Body Channel Communication

Body channel communication (BCC) uses the human body to carry signals, and therefore provides communication and localization that are directly tied to human presence and actions. Previous BCC systems were expensive, could operate only in a laboratory, or only focused on special use cases. We present here an end-to-end BCC system that is designed for ambient intelligence. We introduce the BCC infrastructure that consists of portable devices (e.g., a simple sphere), mobile devices (e.g.,a smartwatch-like wristband), and stationary devices (e.g., floor/wall tiles). We also describe the core technology that is used in each of these units. The TouchCom hardware-software platform…

Wall++: Room-Scale Interactive and Context-Aware Sensing

Human environments are typified by walls – homes, offices, schools, museums, hospitals and pretty much every indoor context one can imagine has walls. In many cases, they make up a majority of readily accessible indoor surface area, and yet they are static – their primary function is to be a wall, separating spaces and hiding infrastructure. We present Wall++, a low-cost sensing approach that allows walls to become a smart infrastructure. Instead of merely separating spaces, walls can now enhance rooms with sensing and interactivity. Our wall treatment and sensing hardware can track users’ touch and gestures, as well as…

Force Jacket: Pneumatically-Actuated Jacket for Embodied

Immersive experiences seek to engage the full sensory system in ways that words, pictures, or touch alone cannot. With respect to the haptic system, however, physical feedback has been provided primarily with handheld tactile experiences or vibration-based designs, largely ignoring both pressure receptors and the full upper-body area as conduits for expressing meaning that is consistent with sight and sound. We extend the potential for immersion along these dimensions with the Force Jacket, a novel array of pneumatically-actuated airbags and force sensors that provide precisely directed force and high frequency vibrations to the upper body. We describe the pneumatic hardware…

Design and Fabrication of a Soft Robotic Hand and Arm System

We present the hardware design and fabrication of a soft arm and hand for physical human-robot interaction. The six DOF arm has two air-filled force sensing modules which passively absorb impact and provide contact force feedback. The arm has an inflated outer cover which encloses the arm’s underlying mechanisms and force sensing modules. An internal projector projects a display on the inside of the cover which is visible from the outside. On the end of the arm is a 3D printed hand with air-filled, force sensing fingertips. We validate the efficacy of the outer cover design by bending the arm…

Stickman: Towards a Human Scale Acrobatic Robot

Human performers have developed impressive acrobatic techniques over thousands of years of practicing the gymnastic arts. At the same time, robots have started to become more mobile and autonomous, and can begin to imitate these stunts in dramatic and informative ways. We present a simple two degree of freedom robot that uses a gravity-driven pendulum launch and produces a variety of somersaulting stunts. The robot uses an IMU and a laser range-finder to estimate its state mid-flight and actuates to change its motion both on and and off the pendulum. We discuss the dynamics of this behavior in a framework…

Automated Deep Reinforcement Learning Environment for Hardware of a Modular Legged Robot

In this paper, we present an automated learning environment for developing control policies directly on the hardware of a modular legged robot. This environment facilitates the reinforcement learning process by computing the rewards using a vision-based tracking system and relocating the robot to the initial position using a resetting mechanism. We employ two state-of-the-art deep reinforcement learning (DRL) algorithms, Trust Region Policy Optimization (TRPO) and Deep Deterministic Policy Gradient (DDPG), to train neural network policies for simple rowing and crawling motions. Using the developed environment, we demonstrate both learning algorithms can effectively learn policies for simple locomotion skills on highly…

Computational Design of Robotic Devices from High-Level Motion Specifications

We present a novel computational approach to designing robotic devices from high-level motion specifications. Our computational system uses a library of modular components— actuators, mounting brackets, and connectors—to define the space of possible robot designs. The process of creating a new robot begins with a set of input trajectories that specify how its end effectors and/or body should move. By searching through the combinatorial set of possible arrangements of modular components, our method generates a functional, as-simple-as possible robotic device that is capable of tracking the input motion trajectories. To significantly improve the efficiency of this discrete optimization process, we…

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