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Dive into the research topics where Robert K. Katzschmann is active.

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Featured researches published by Robert K. Katzschmann.


Soft robotics | 2015

A Recipe for Soft Fluidic Elastomer Robots

Andrew D. Marchese; Robert K. Katzschmann; Daniela Rus

Abstract This work provides approaches to designing and fabricating soft fluidic elastomer robots. That is, three viable actuator morphologies composed entirely from soft silicone rubber are explored, and these morphologies are differentiated by their internal channel structure, namely, ribbed, cylindrical, and pleated. Additionally, three distinct casting-based fabrication processes are explored: lamination-based casting, retractable-pin-based casting, and lost-wax-based casting. Furthermore, two ways of fabricating a multiple DOF robot are explored: casting the complete robot as a whole and casting single degree of freedom (DOF) segments with subsequent concatenation. We experimentally validate each soft actuator morphology and fabrication process by creating multiple physical soft robot prototypes.


intelligent robots and systems | 2015

Haptic identification of objects using a modular soft robotic gripper

Bianca S. Homberg; Robert K. Katzschmann; Mehmet Remzi Dogar; Daniela Rus

This work presents a soft hand capable of robustly grasping and identifying objects based on internal state measurements. A highly compliant hand allows for intrinsic robustness to grasping uncertainty, but the specific configuration of the hand and object is not known, leaving undetermined if a grasp was successful in picking up the right object. A soft finger was adapted and combined to form a three finger gripper that can easily be attached to existing robots, for example, to the wrist of the Baxter robot. Resistive bend sensors were added within each finger to provide a configuration estimate sufficient for distinguishing between a set of objects. With one data point from each finger, the object grasped by the gripper can be identified. A clustering algorithm to find the correspondence for each grasped object is presented for both enveloping grasps and pinch grasps. This hand is a first step towards robust proprioceptive soft grasping.


international symposium on experimental robotics | 2016

Hydraulic Autonomous Soft Robotic Fish for 3D Swimming

Robert K. Katzschmann; Andrew D. Marchese; Daniela Rus

This work presents an autonomous soft-bodied robotic fish that is hydraulically actuated and capable of sustained swimming in three dimensions. The design of a fish-like soft body has been extended to deform under hydraulic instead of pneumatic power. Moreover, a new closed-circuit drive system that uses water as a transmission fluid is used to actuate the soft body. Circulation of water through internal body channels provides control over the fish’s caudal fin propulsion and yaw motion. A new fabrication technique for the soft body is described, which allows for arbitrary internal fluidic channels, enabling a wide-range of continuous body deformations. Furthermore, dynamic diving capabilities are introduced through pectoral fins as dive planes. These innovations enable prolonged fish-like locomotion in three dimensions.


international conference on robotics and automation | 2016

Printable hydraulics: A method for fabricating robots by 3D co-printing solids and liquids

Robert MacCurdy; Robert K. Katzschmann; Youbin Kim; Daniela Rus

This paper introduces a novel technique for fabricating functional robots using 3D printers. Simultaneously depositing photopolymers and a non-curing liquid allows complex, pre-filled fluidic channels to be fabricated. This new printing capability enables complex hydraulically actuated robots and robotic components to be automatically built, with no assembly required. The technique is showcased by printing linear bellows actuators, gear pumps, soft grippers and a hexapod robot, using a commercially-available 3D printer. We detail the steps required to modify the printer and describe the design constraints imposed by this new fabrication approach.


Soft robotics | 2015

Autonomous Object Manipulation Using a Soft Planar Grasping Manipulator

Robert K. Katzschmann; Andrew D. Marchese; Daniela Rus

Abstract This article presents the development of an autonomous motion planning algorithm for a soft planar grasping manipulator capable of grasp-and-place operations by encapsulation with uncertainty in the position and shape of the object. The end effector of the soft manipulator is fabricated in one piece without weakening seams using lost-wax casting instead of the commonly used multilayer lamination process. The soft manipulation system can grasp randomly positioned objects within its reachable envelope and move them to a desired location without human intervention. The autonomous planning system leverages the compliance and continuum bending of the soft grasping manipulator to achieve repeatable grasps in the presence of uncertainty. A suite of experiments is presented that demonstrates the systems capabilities.


intelligent robots and systems | 2014

Whole arm planning for a soft and highly compliant 2D robotic manipulator

Andrew D. Marchese; Robert K. Katzschmann; Daniela Rus

Soft continuum manipulators have the advantage of being more compliant and having more degrees of freedom than rigid redundant manipulators. This attribute should allow soft manipulators to autonomously execute highly dexterous tasks. However, current approaches to motion planning, inverse kinematics, and even design limit the capacity of soft manipulators to take full advantage of their inherent compliance. We provide a computational approach to whole arm planning for a soft planar manipulator that advances the arms end effector pose in task space while simultaneously considering the arms entire envelope in proximity to a confined environment. The algorithm solves a series of constrained optimization problems to determine locally optimal inverse kinematics. Due to inherent limitations in modeling the kinematics of a highly compliant soft robot and the local optimality of the planners solutions, we also rely on the increased softness of our newly designed manipulator to accomplish the whole arm task, namely the arms ability to harmlessly collide with the environment. We detail the design and fabrication of the new modular manipulator as well as the planners central algorithm. We experimentally validate our approach by showing that the robotic system is capable of autonomously advancing the soft arm through a pipe-like environment in order to reach distinct goal states.


international conference on robotics and automation | 2017

Enabling independent navigation for visually impaired people through a wearable vision-based feedback system

Hsueh-Cheng Wang; Robert K. Katzschmann; Santani Teng; Brandon Araki; Laura Giarré; Daniela Rus

This work introduces a wearable system to provide situational awareness for blind and visually impaired people. The system includes a camera, an embedded computer and a haptic device to provide feedback when an obstacle is detected. The system uses techniques from computer vision and motion planning to (1) identify walkable space; (2) plan step-by-step a safe motion trajectory in the space, and (3) recognize and locate certain types of objects, for example the location of an empty chair. These descriptions are communicated to the person wearing the device through vibrations. We present results from user studies with low- and high-level tasks, including walking through a maze without collisions, locating a chair, and walking through a crowded environment while avoiding people.


Science Robotics | 2018

Exploration of underwater life with an acoustically controlled soft robotic fish

Robert K. Katzschmann; Joseph DelPreto; Robert MacCurdy; Daniela Rus

A soft robot fish swims independently in three dimensions and enables studies of aquatic life in natural coral reef habitats. Closeup exploration of underwater life requires new forms of interaction, using biomimetic creatures that are capable of agile swimming maneuvers, equipped with cameras, and supported by remote human operation. Current robotic prototypes do not provide adequate platforms for studying marine life in their natural habitats. This work presents the design, fabrication, control, and oceanic testing of a soft robotic fish that can swim in three dimensions to continuously record the aquatic life it is following or engaging. Using a miniaturized acoustic communication module, a diver can direct the fish by sending commands such as speed, turning angle, and dynamic vertical diving. This work builds on previous generations of robotic fish that were restricted to one plane in shallow water and lacked remote control. Experimental results gathered from tests along coral reefs in the Pacific Ocean show that the robotic fish can successfully navigate around aquatic life at depths ranging from 0 to 18 meters. Furthermore, our robotic fish exhibits a lifelike undulating tail motion enabled by a soft robotic actuator design that can potentially facilitate a more natural integration into the ocean environment. We believe that our study advances beyond what is currently achievable using traditional thruster-based and tethered autonomous underwater vehicles, demonstrating methods that can be used in the future for studying the interactions of aquatic life and ocean dynamics.


intelligent robots and systems | 2013

Towards online trajectory generation considering robot dynamics and torque limits

Robert K. Katzschmann; Torsten Kröger; Tamim Asfour; Oussama Khatib

Generating robot motion trajectories instantaneously in the moment unforeseen sensor events happen is very essential for many real-world robot applications. Using a previous work on online trajectory generation as a basis, this paper proposes an alternative approach that also considers dynamic models. The former class of algorithms does not take into account dynamically changing acceleration capabilities based on maximum actuator forces/torques. This paper extends target velocity-based algorithms of the previous approach by taking into consideration the entire system dynamics when generating trajectories online within one control cycle (typically 1 ms or less). The extension includes the acceleration capabilities of a robot at every discrete time step assuming constant values for the maximum actuator forces/torques, thus allowing the generation of adaptive trajectory profiles during the motion of the robot. Several real-world experimental results using a seven-degree-of-freedom lightweight robot arm underline the relevance of this extension.


intelligent robots and systems | 2016

Cyclic hydraulic actuation for soft robotic devices

Robert K. Katzschmann; Austin de Maille; David L. Dorhout; Daniela Rus

Undulating structures are one of the most diverse and successful forms of locomotion in nature, both on ground and in water. This paper presents a comparative study for actuation by undulation in water. We focus on actuating a 1DOF systems with several mechanisms. A hydraulic pump attached to a soft body allows for water movement between two inner cavities, ultimately leading to a flexing actuation in a side-to-side manner. The effectiveness of six different, self-contained designs based on centrifugal pump, flexible impeller pump, external gear pump and rotating valves are compared. These hydraulic actuation systems combined with soft test bodies were then measured at a lower and higher oscillation frequency. The deflection characteristics of the soft body, the acoustic noise of the pump and the overall efficiency of the system are recorded. A brushless, centrifugal pump combined with a novel rotating valve performed at both test frequencies as the most efficient pump, producing sufficiently large cyclic body deflections along with the least acoustic noise among all pumps tested. An external gear pump design produced the largest body deflection, but consumes an order of magnitude more power and produced high noise levels. Further refinement remains on determining the suitable oscillation frequencies and inner cavity designs for optimal efficiency and movement.

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Daniela Rus

Massachusetts Institute of Technology

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Andrew D. Marchese

Massachusetts Institute of Technology

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Bianca S. Homberg

Massachusetts Institute of Technology

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Brandon Araki

Massachusetts Institute of Technology

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Joseph DelPreto

Massachusetts Institute of Technology

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Austin de Maille

Massachusetts Institute of Technology

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David L. Dorhout

Massachusetts Institute of Technology

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Hsueh-Cheng Wang

Massachusetts Institute of Technology

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Mehmet Remzi Dogar

Massachusetts Institute of Technology

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