Jeffrey I. Lipton

RO
h-index11
4papers
228citations
Novelty46%
AI Score41

4 Papers

5.0ROApr 29
Electrostatic Clutch-Based Mechanical Multiplexer with Increased Force Capability

Timothy E. Amish, Jeffrey T. Auletta, Chad C. Kessens et al.

Robotic systems with many degrees of freedom (DoF) are constrained by the demands of dedicating a motor to each joint, and while mechanical multiplexing reduces actuator count, existing clutch designs are bulky, force-limited, or restricted to one output at a time. The problem addressed in this study is how to achieve high-force multiplexing that supports both simultaneous and sequential control from a single motor. Here we show an electrostatic capstan clutch-based transmission that enables both single-input-single-output (SISO) and single-input-multiple-output (SIMO) multiplexing. We demonstrated these on a four-DoF tendon-driven robotic hand where a single motor achieved output forces of up to 212 N, increased vertical grip strength by 4.09 times, and raised horizontal carrying capacity to 111.2 N, the highest currently among five-fingered tendon-driven robotic hands. These results demonstrate that electrostatic-based multiplexing provides versatile actuation, overcoming the limitations of prior systems.

5.3RODec 9, 2021
Kinematic Modeling of Handed Shearing Auxetics via Piecewise Constant Curvature

Aman Garg, Ian Good, Daniel Revier et al.

Handed Shearing Auxetics (HSA) are a promising technique for making motor-driven, soft, continuum robots. Many potential applications from inspection tasks to solar tracking require accurate kinematic models to predict the position and orientation of these structures. Currently there are no models for HSA based continuum platforms. To address this gap we propose to adapt Piecewise Constant Curvature (PCC) Models using a length change coupling matrix. This models the interaction of HSA structures in a 2x2 array. The coupling matrix maps the change in motor angles to length changes and defines the configuration space in our modified PCC Model. We evaluate our model on a composite movement encompassing bending, extension and compression behavior. Our model achieves a positional accuracy with mean error of 5.5mm or 4.5% body length and standard deviation of 1.72mm. Further, we achieve an angular accuracy with mean error of -2.8$^\circ$ and standard deviation of 1.9$^\circ$.

3.0ROOct 1, 2021
Expanding the Design Space for Electrically-Driven Soft Robots through Handed Shearing Auxetics

Ian Good, Tosh Brown-Moore, Aditya Patil et al.

Handed Shearing Auxetics (HSA) are a promising structure for making electrically driven robots with distributed compliance that convert a motors rotation and torque into extension and force. We overcame past limitations on the range of actuation, blocked force, and stiffness by focusing on two key design parameters: the point of an HSA's auxetic trajectory that is energetically preferred, and the number of cells along the HSAs length. Modeling the HSA as a programmable spring, we characterize the effect of both on blocked force, minimum energy length, spring constant, angle range and holding torque. We also examined the effect viscoelasticity has on actuation forces over time. By varying the auxetic trajectory point, we were able to make actuators that can push, pull, or do both. We expanded the range of forces possible from 5N to 150N, and the range of stiffness from 2 N/mm to 89 N/mm. For a fixed point on the auxetic trajectory, we found decreasing length can improve force output, at the expense of needing higher torques, and having a shorter throw. We also found that the viscoelastic effects can limit the amount of force a 3D printed HSA can apply over time.

20.4ROMar 3, 2017
Baxter's Homunculus: Virtual Reality Spaces for Teleoperation in Manufacturing

Jeffrey I Lipton, Aidan J Fay, Daniela Rus

Expensive specialized systems have hampered development of telerobotic systems for manufacturing systems. In this paper we demonstrate a telerobotic system which can reduce the cost of such system by leveraging commercial virtual reality(VR) technology and integrating it with existing robotics control software. The system runs on a commercial gaming engine using off the shelf VR hardware. This system can be deployed on multiple network architectures from a wired local network to a wireless network connection over the Internet. The system is based on the homunculus model of mind wherein we embed the user in a virtual reality control room. The control room allows for multiple sensor display, dynamic mapping between the user and robot, does not require the production of duals for the robot, or its environment. The control room is mapped to a space inside the robot to provide a sense of co-location within the robot. We compared our system with state of the art automation algorithms for assembly tasks, showing a 100% success rate for our system compared with a 66% success rate for automated systems. We demonstrate that our system can be used for pick and place, assembly, and manufacturing tasks.