Daniel Aukes — accepted AI-conference papers

2020

Kinematic Modeling and Trajectory Tracking Control of an Octopus-Inspired Hyper-Redundant Robot

Amir Salimi Lafmejani, Azadeh Doroudchi, Hamed Farivarnejad, Ximin He, Daniel Aukes, Matthew M. Peet +3

RA-L 2020

This letter addresses the kinematic modeling and control of hyper-redundant robots inspired by the octopus arm. We propose a discrete multi-segment model in which each segment is a 6-DoF Gough-Stewart parallel platform. Our model is novel in that it can reproduce all generic motions of an octopus ar

Cited by 41 Source ↗Scholar ↗

2017

From the Lab to the Desert: Fast Prototyping and Learning of Robot Locomotion

Kevin Sebastian Luck, Joseph Campbell, Michael Jansen, Daniel Aukes, Heni Ben Amor

RSS 2017poster

We present a methodology for fast prototyping of morphologies and controllers for robot locomotion. Going beyond simulation-based approaches, we argue that the form and function of a robot, as well as their interplay with real-world environmental conditions are critical. Hence, fast design and learn…

Cited by 30 Source ↗PDF ↗Scholar ↗

2015

Model driven design for flexure-based Microrobots

Neel Doshi, Benjamin Goldberg, Ranjana Sahai, Noah Jafferis, Daniel Aukes, Robert J. Wood +1

IROS 2015poster

This paper presents a non-linear, dynamic model of the flexure-based transmission in the Harvard Ambulatory Microrobot (HAMR). The model is derived from first principles and has led to a more comprehensive understanding of the components in this transmission. In particular, an empirical model of the…

Cited by 72 Source ↗Scholar ↗