Marc D. Killpack — accepted AI-conference papers

2024

Learning Dynamic Tasks on a Large-scale Soft Robot in a Handful of Trials

Sicelukwanda Zwane, Daniel Cheney, Curtis C. Johnson, Yicheng Luo, Yasemin Bekiroglu, Marc D. Killpack +1

IROS 2024poster

Soft robots offer more flexibility, compliance, and adaptability than traditional rigid robots. They are also typically lighter and cheaper to manufacture. However, their use in real-world applications is limited due to modeling challenges and difficulties in integrating effective proprioceptive sen…

Cited by 1 Source ↗code ↗Scholar ↗

2023

Soft Robot Shape Estimation: A Load-Agnostic Geometric Method

Christian Sorensen, Marc D. Killpack

IROS 2023poster

In this paper we present a novel kinematic representation of a soft continuum robot to enable full shape estimation using a purely geometric solution. The kinematic representation involves using length varying piecewise constant curvature segments to describe the deformed shape of the robot. Based o…

Cited by 4 Source ↗Scholar ↗

2021

Soft Robot Configuration Estimation and Control Using Simultaneous Localization and Mapping

Christian Sorensen, Phillip Hyatt, Matthew Ricks, Seth Nielsen, Marc D. Killpack

IROS 2021poster

In this paper we present a novel approach to accomplishing soft robot configuration estimation and control using RGB-D cameras and SLAM-based methods. By placing cameras on the unactuated sections of our large-scale (approximately 2 meters long) pneumatic soft robot, we can map an environment and th…

Cited by 4 Source ↗Scholar ↗

2020

Real-Time Nonlinear Model Predictive Control of Robots Using a Graphics Processing Unit

Phillip Hyatt, Marc D. Killpack

RA-L 2020

In past robotics applications, Model Predictive Control (MPC) has often been limited to linear models and relatively short time horizons. In recent years however, research in optimization, optimal control, and simulation has enabled some forms of nonlinear model predictive control which find locally

Cited by 34 Source ↗Scholar ↗

2017

Motion planning for mobile robots using inverse kinematics branching

Daniel M. Bodily, Thomas F. Allen, Marc D. Killpack

ICRA 2017poster

A novel algorithm for planning robotic manipulation tasks is presented in which the base position and joint motions of a robot are simultaneously optimized to follow a smooth desired end-effector trajectory. During the optimization routine, the manipulator's base position and joint motions are plann…

Cited by 34 Source ↗Scholar ↗

2017

Multi-objective design optimization of a soft, pneumatic robot

Daniel M. Bodily, Thomas F. Allen, Marc D. Killpack

ICRA 2017poster

We present a method for the design optimization of a soft, inflatable robot. The method described utilizes a multi-objective fitness function together with custom, platform-specific metrics related to the dexterity and load-bearing capacity of inflatable manipulators. Candidate designs are scored by…

Cited by 43 Source ↗Scholar ↗

2017

Variable stiffness adaptation to mitigate system failure in inflatable robots

Joshua P. Wilson, Charles M. Best, Marc D. Killpack

ICRA 2017poster

Although inflatable soft robots are not yet a common robot platform, air leaking from the internal structure is a common and undesirable mode of failure for these platforms. In this paper we demonstrate a method to detect leaks in the structural chamber of an inflatable, pneumatically actuated robot…

Cited by 5 Source ↗Scholar ↗

2016

Simultaneous position and stiffness control for an inflatable soft robot

Morgan T. Gillespie, Charles M. Best, Marc D. Killpack

ICRA 2016

Soft robot research has led to the development of platforms that should allow for better performance when working in uncertain or dynamic environments. The potential improvement in performance of these platforms ranges from mechanical robustness to high forces, to applying lower incidental contact f

Cited by 76 Source ↗Scholar ↗