We investigate the use of 3-dimensional (3D) force sensors in a prosthetic hand. 3D force sensing in prostheses can be used to incorporate intelligent grasping capabilities, allowing the hand to automatically adjust its grasp or release an object. This can significantly decrease the burden on the user and increase functionality of the prosthesis. Coupled with an underactuated hand, this opens up possibilities for highly functional, affordable prosthetic hands. In this work, we present our design of 3D magnetic force sensors that are embedded within the fingers of an open-source, 3D printable underactuated hand. We implement a simple control scheme using both shear and normal force readings to automate grasp release. Finally, we combine this force control with EMG grasp detection for a series of pick-and-place tasks. Preliminary results suggest that intelligent grasp control imposes less of a burden on the user than a completely EMG-based grasp control.
The human hand serves as an inspiration for robotic grippers. However, the dimensions of the human hand evolved under a different set of constraints and requirements than that of robots today. This paper discusses a method of kinematically optimizing the design of an anthropomorphic robotic hand. We focus on maximizing the workspace intersection of the thumb and the other fingers as well as maximizing the size of the largest graspable object. We perform this optimization and use the resulting dimensions to construct a flexible, underactuated 3D printed prototype. We verify the results of the optimization through experimentation, demonstrating that the optimized hand is capable of grasping objects ranging from less than 1 mm to 12.8 cm in diameter with a high degree of reliability. The hand is lightweight and inexpensive, weighing 333 g and costing less than 175 USD, and strong enough to lift over 1.1 lb (500 g). We demonstrate that the optimized hand outperforms an open-source 3D printed anthropomorphic hand on multiple tasks. Finally, we demonstrate the performance of our hand by employing a classification-based user intent decision system which predicts the grasp type using real-time electromyographic (EMG) activity patterns.
Ann Marie Votta, Raagini Rameshwar, Erik Skorina
Soft robots are theoretically well-suited to rescue and exploration applications where their flexibility allows
for the traversal of highly cluttered environments. However, most existing mobile soft robots are not fast
or powerful enough to effectively traverse three-dimensional environments. In this paper, we introduce a new mobile
robot with a continuously deformable slender body structure, the SalamanderBot, which combines the flexibility and
maneuverability of soft robots, with the speed and power of traditional mobile robots. It consists of a cable-driven
bellows-like origami module based on the Yoshimura crease pattern mounted between sets of powered wheels. The origami
structure allows the body to deform as necessary to adapt to complex environments and terrains, while the wheels
allow the robot to reach speeds of up to 303.1 mm/s (2.05 body-length/s). Salamanderbot can climb up to 60-degree
slopes and perform sharp turns with a minimum turning radius of 79.9 mm (0.54 body-length).
We are working on a teleoperation system with safe, realistic force feedback for intuitive control
of a robotic arm and anthropomorphic robotic hand as its end effector. The system interfaces with the
user via a novel soft robotic data glove. Our haptic glove detects the state of the hand using inertial
measurement units (IMUs) and custom curvature sensors without the need for any external tracking system,
and employs pneumatic muscles to provide force feedback.
The glove itself weighs only 58 grams, and the glove combined with IMUs and tether weighs only 213 grams.
We use this glove to control a Kinova Jaco robotic arm and a custom 3D printed hand with embedded force
Soft materials are particularly suited for wearable systems as they provide a safe and comfortable
means for human-robot interaction. In this research, we apply soft robotics to the problem of robot
arm teleoperation, particularly regarding haptic feedback.
To provide realistic force feedback, we have developed "haptic muscles", soft pneumatic pouches that fit around the user's fingers. When a pouch inflates, it applies a gentle pressure to the user's knuckles, keeping the hand open. This imitates how a grasped object would prevent your fingers from closing, by instead pushing the fingers open.
Raagini Rameshwar, Ann Marie Votta, Erik Skorina
Multi-Robot Object Transport without Communication
We present a novel approach to achieve decentralized distribution of forces in a multirobot system. In this approach,
each robot in the group relies on the behavior of a cooperative virtual teammate that is defined independent of the
population and formation of the real team. Consequently, such formulation eliminates the need for inter-agent communications
or leader–follower architectures. In particular, effectiveness of the method is studied in a collective manipulation
problem where the objective is to control the position and orientation of a body in time. To experimentally validate
the performance of the proposed method, a new swarm agent, Δρ (Delta-Rho), is introduced. A multirobot system,
consisting of five Δρ agents, is then utilized as the experimental setup. The obtained results are also compared with
a norm-optimal centralized controller by quantitative metrics. Experimental results prove the performance of the
algorithm in different tested scenarios and demonstrate a scalable, versatile, and robust system-level behavior.
Soft pneumatic actuators enable robots to interact safely with complex environments, but often suffer from imprecise control and unpredictable dynamics. This research addresses these challenges through the use of model reference adaptive control, which modulates the input to the plant to ensure that it behaves similarly to a reference dynamic model. We use adaptive control to standardize the performance of soft actuators and eliminate their nonlinear behavior. We implement an adaptive controller chosen for its simplicity and efficiency, and study the ability of this controller to force different soft pneumatic actuators to behave uniformly under a variety of conditions. Next, we formulate an inverse dynamic feedforward controller, allowing soft actuators to quickly follow reference trajectories. We test the performance of the proposed feedforward controller with and without the adaptive controller, to study its open-loop effectiveness and highlight the improvements the adaptive controller offers. Our experimental results indicate that soft actuators can follow unstructured continuous signals through the use of the proposed adaptive control approach.
Erik H. Skorina, Yinan Sun, Ming Luo, Weijia Tao, Fuchen Chen, Selim Ozel
This work focuses on an origami-inspired cable-driven continuum manipulator module that offers low-cost, low-volume deployment, light weight, and inherently safe human interaction and collaboration. Each module has a mass of around 110 g and integrates the actuation, sensing, and control sub-systems necessary for operation. The origami structure has 7.311 Nm/rad (0.128 Nm/degree) torsional stiffness while being capable of bending in two directions and changing arclength down to a fully collapsed state. A maximum contraction of 35 mm and bending angle of 35.5 degrees were achieved with 45 mm arc length. The module is capable of passively supporting a 1-kg mass at its tip, or 4 additional serially connected modules, bending approximately 6 degrees in the worst case. We also show that we can actively compensate for external moments by pre-compressing or pre-bending the module. We utilize an inverse kinematic control scheme and use it for both open and closed loop control following a circular trajectory. Our results indicate that the module motion follows the desired trajectory with an RMS error of 0.681 mm in the horizontal (x-y) plane and 0.373 mm in the z-axis with closed-loop control. We also assembled two origami modules in series and drove them independently, demonstrating the proof-of-concept of a modular origami continuum manipulator.
Shou-Shan Chiang, Junius Santoso, Ruibo Yan
This research project focuses on the development of a lightweight origami-inspired foldable hexapod robot platform.
Taking advantage of origami techniques in design, the robot can be fabricated and assembled in less than one hour from scratch. In order to increase the fabrication process and reduce the final cost, the crease
pattern of the robot includes built-in fasteners to eliminate the need of any external screws and nuts. The locomotion engine of the platform composes of two 6-bar mechanisms. Each mechanism drives three feet of the
robot through an optimized gait sequence. Design flexibility, ease of fabrication, and low cost make the robot suitable as an agent for swarm objectives. Experimental results of the robot show a maximum forward speed
of 5 body lengths per second and maximum angular velocity of 1 revolution per second. The final prototype weighs only 42 grams.
We developed a new generation of fluidic elastomer actuators (FEAs) that offer bidirectional bending as motion segments of a pressure-operated soft robotic snake.
Our prior work on FEAs has identified a number of limitations, namely a high center of gravity, narrow base,
slow dynamics, and a small range of pressure inputs. We developed two versions of FEAs based on an improved
design concept with different geometric parameters and characterized their dynamic response under a custom
visual tracking system. Compared with the previous actuators, the FEAs developed in this work offer robust
operation, safety at larger input pressure values, faster response, lower center of gravity and a flat bottom
for better compatibility for snake-like undulatory locomotion.
For a mobile robot undergoing serpentine locomotion, an accurate dynamic model is a fundamental requirement for optimization,
control, navigation, and learning algorithms. Such algorithms can be readily implemented for traditional rigid robots, but remain
a challenge for nonlinear and low-bandwidth soft robotic systems. Our work addresses the theoretical modeling of the dynamics
of a pressure-operated soft snake robot. A general framework is detailed to solve the 2D modeling problem of a soft snake robot,
which is applicable to most pressure-operated soft robots developed by a modular kinematic arrangement of bending-type fluidic
elastomer actuators. The model is simulated using measured physical parameters of a soft snake robot prototype. The theoretical
results are verified through a detailed comparison to locomotion experiments on a flat surface with measured frictional properties.
Yinan Sun, Ming Luo, Mahdi Agheli, Selim Ozel, Weijia Tao