arXiv subjects

Matthew Travers

Publications and source records attributed to Matthew Travers.

21 records · Page 2Linked to original sources

arXiv2018

Trajectory Generation for Millimeter Scale Ferromagnetic Swimmers: Theory and Experiments

Microrobots have the potential to impact many areas such as microsurgery, micromanipulation and minimally invasive sensing. Due to their small size, microrobots swim in a regime that is governed by low Reynolds number hydrodynamics. In this paper, we consider small scale artificial swimmers that are fabricated using ferromagnetic filaments and locomote in response to time varying external magnetic fields. We motivate the design of previously proposed control laws using tools from geometric mechanics and also demonstrate how new control laws can be synthesized to generate net translation in such swimmers. We further describe how to modify these control inputs to make the swimmers track rich trajectories in the workspace by investigating stability properties of their limit cycles in the orientation angles phase space. Following a systematic design optimization, we develop a principled approach to encode internal magnetization distributions in millimeter scale ferromagnetic filaments. We verify and demonstrate this procedure experimentally and finally show translation, trajectory tracking and turning in place locomotion in these optimal swimmers using a Helmholtz coils setup.

eess.SY↗

arXiv2018

Learning to Sequence Robot Behaviors for Visual Navigation

Recent literature in the robotics community has focused on learning robot behaviors that abstract out lower-level details of robot control. To fully leverage the efficacy of such behaviors, it is necessary to select and sequence them to achieve a given task. In this paper, we present an approach to both learn and sequence robot behaviors, applied to the problem of visual navigation of mobile robots. We construct a layered representation of control policies composed of low- level behaviors and a meta-level policy. The low-level behaviors enable the robot to locomote in a particular environment while avoiding obstacles, and the meta-level policy actively selects the low-level behavior most appropriate for the current situation based purely on visual feedback. We demonstrate the effectiveness of our method on three simulated robot navigation tasks: a legged hexapod robot which must successfully traverse varying terrain, a wheeled robot which must navigate a maze-like course while avoiding obstacles, and finally a wheeled robot navigating in the presence of dynamic obstacles. We show that by learning control policies in a layered manner, we gain the ability to successfully traverse new compound environments composed of distinct sub-environments, and outperform both the low-level behaviors in their respective sub-environments, as well as a hand-crafted selection of low-level policies on these compound environments.

cs.RO↗

arXiv2014

Sidewinding with minimal slip: Snake and robot ascent of sandy slopes

Limbless organisms such as snakes can navigate nearly all terrain. In particular, desert-dwelling sidewinder rattlesnakes (Crotalus cerastes) operate effectively on inclined granular media (such as sand dunes) that induce failure in field-tested limbless robots through slipping and pitching. Our laboratory experiments reveal that as granular incline angle increases, sidewinder rattlesnakes increase the length of their body in contact with the sand. Implementing this strategy in a physical robot model of the snake enables the device to ascend sandy slopes close to the angle of maximum slope stability. Plate drag experiments demonstrate that granular yield stresses decrease with increasing incline angle. Together, these three approaches demonstrate how sidewinding with contact-length control mitigates failure on granular media.

physics.bio-ph↗