Author name cluster

Jonathan Fink

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

20 papers

1 author row

ICRA Conference 2022 Conference Paper

Active Learning for Testing and Evaluation in Field Robotics: A Case Study in Autonomous, Off-Road Navigation

Jason M. Gregory
Daniel M. Sahu
Eli S. Lancaster
Felix A. Sanchez
Trevor Rocks
Brian Kaukeinen
Jonathan Fink
Satyandra K. Gupta

Testing and evaluation of field robotic systems requires both experimentation in representative conditions and human supervision to effectively assess components, manage risk, and interpret results. Due to the complexity of robotic sys-tems, we argue this experimentation should be done adaptively by using insights gained from previous trials. Furthermore, we envision an advisory system that could assist experimenters with selecting trial configurations by learning and accounting for human preferences and risk tolerances; however, formal methods for human decision making in the context of field robotic experimentation remains an open question. In this work, we present and analyze a case study for how decisions were made during the testing and evaluation of an off-road, autonomous navigation system. From the perspective of active learning, we find that Bayesian Optimization is a promising mathematical framework for modeling human decision making in adaptive experimental design of field robotics and that a combination of the EI, KG, and PES acquisition functions would likely be useful for realizing an advisory system.

IROS Conference 2022 Conference Paper

Risk-Aware Off-Road Navigation via a Learned Speed Distribution Map

Xiaoyi Cai
Michael Everett
Jonathan Fink
Jonathan P. How

Motion planning in off-road environments re-quires reasoning about both the geometry and semantics of the scene (e. g. , a robot may be able to drive through soft bushes but not a fallen log). In many recent works, the world is classified into a finite number of semantic categories that often are not sufficient to capture the ability (i. e. , the speed) with which a robot can traverse off-road terrain. Instead, this work proposes a new representation of traversability based exclusively on robot speed that can be learned from data, offers interpretability and intuitive tuning, and can be easily integrated with a variety of planning paradigms in the form of a costmap. Specifically, given a dataset of experienced trajectories, the proposed algorithm learns to predict a distribution of speeds the robot could achieve, conditioned on the environment semantics and commanded speed. The learned speed distribution map is converted into costmaps with a risk-aware cost term based on conditional value at risk (CVaR). Numerical simulations demonstrate that the proposed risk-aware planning algorithm leads to faster average time-to-goals compared to a method that only considers expected behavior, and the planner can be tuned for slightly slower, but less variable behavior. Furthermore, the approach is integrated into a full autonomy stack and demonstrated in a high-fidelity Unity environment and is shown to provide a 30% improvement in the success rate of navigation.

ICRA Conference 2020 Conference Paper

Mobile Wireless Network Infrastructure on Demand

Daniel Mox
Miguel Calvo-Fullana
Mikhail Gerasimenko
Jonathan Fink
Vijay Kumar 0001
Alejandro Ribeiro

In this work, we introduce Mobile Wireless Infrastructure on Demand: a framework for providing wireless connectivity to multi-robot teams via autonomously reconfiguring ad-hoc networks. In many cases, previous multi-agent systems either assumed the availability of existing communication infrastructure or were required to create a network in addition to completing their objective. Instead our system explicitly assumes the responsibility of creating and sustaining a wireless network capable of satisfying end-to-end communication requirements of a team of agents, called the task team, performing an arbitrary objective. To accomplish this goal, we propose a joint optimization framework that alternates between finding optimal network routes to support data flows between the task agents and improving the performance of the network by repositioning a collection of mobile relay nodes referred to as the network team. We demonstrate our approach with simulations and experiments wherein wireless connectivity is provided to patrolling task agents.

ICRA Conference 2020 Conference Paper

Test Your SLAM! The SubT-Tunnel dataset and metric for mapping

John G. Rogers
Jason M. Gregory
Jonathan Fink
Ethan Stump

This paper presents an approach and introduces new open-source tools that can be used to evaluate robotic mapping algorithms. Also described is an extensive subterranean mine rescue dataset based upon the DARPA Subterranean (SubT) challenge including professionally surveyed ground truth. Finally, some commonly available approaches are evaluated using this metric.

ICRA Conference 2016 Conference Paper

Hybrid architecture for communication-aware multi-robot systems

James Stephan
Jonathan Fink
Vijay Kumar 0001
Alejandro Ribeiro

In this paper we propose a hybrid architecture that allows a team of mobile robots to self-organize into a multi-hop ad-hoc network and solve the joint mobility and communication problem in complex environments to complete a given task. The system consists of an outer global planning loop and an inner local loop responsible for motion and network routing, arranged in a two-stage feedback system. This system is able to leverage the benefits of previous systems, while avoiding their drawbacks. This results in a lightweight responsive system that is able to operate in complex environments with minimal global coordination while maintaining a minimum end-to-end data rate between robots. Two main benefits of our approach are demonstrated through experimentation superior performance over existing systems and dynamic adjustment to unexpected events. We conclude with a demonstration of the system operating in a realistic scenario, in which the team patrols a set of hallways.

IROS Conference 2016 Conference Paper

Online learning for characterizing unknown environments in ground robotic vehicle models

Alec Koppel
Jonathan Fink
Garrett Warnell
Ethan Stump
Alejandro Ribeiro

In pursuit of increasing the operational tempo of a ground robotics platform in unknown domains, we consider the problem of predicting the distribution of structural state-estimation error due to poorly-modeled platform dynamics as well as environmental effects. Such predictions are a critical component of any modern control approach that utilizes uncertainty information to provide robustness in control design. We use an online learning algorithm based on matrix factorization techniques to fit a statistical model of error that provides enough expressive power to enable prediction directly from motion control signals and low-level visual features. Moreover, we empirically demonstrate that this technique compares favorably to predictors that do not incorporate this information.

IROS Conference 2016 Conference Paper

Towards online characterization of autonomously navigating robots in unstructured environments

Jeffrey N. Twigg
Jason M. Gregory
Jonathan Fink

Autonomous platforms are confronted by a diversity of challenges in unstructured environments, which make monitoring performance a non-trivial task. Some of these environments are so complex that they preclude persistent, nearby operator oversight. This absence of oversight motivates the need for an online monitoring system, specifically for robots operating in difficult environments. We develop a test methodology and set of online monitoring metrics by extending methods for characterizing robotic-systems using offline metrics. We implement this test methodology in an unstructured, outdoor environment and show the resulting performance information gained from our online monitoring solution. This online monitoring approach is generalizable such that it characterizes any robotic system that meets our set of hardware and software criteria.

IROS Conference 2014 Conference Paper

Experimental analysis of models for trajectory generation on tracked vehicles

Jonathan Fink
Ethan Stump

We begin to bridge the gap between high-level motion planning and execution by adopting models to abstract the complicated skid-steer vehicle dynamics and evaluating their suitability as motion predictors for a feed-forward control framework. We consider three kinematic motion models and a drivetrain model in experiments on two surface types with a small tracked vehicle. We perform statistical analysis of the predictive accuracy of these models when used to create optimal open-loop plans for a set of canonical maneuvers and discuss the applicability of these models for a closed-loop control framework.

IROS Conference 2014 Conference Paper

Robust routing and Multi-Confirmation Transmission Protocol for connectivity management of mobile robotic teams

James Stephan
Jonathan Fink
Benjamin Charrow
Alejandro Ribeiro
Vijay Kumar 0001

Providing reliable end-to-end communication for teams of robots requires the integration of novel routing techniques, motion planning algorithms, and transport level communication protocols. In this paper we look at existing robust routing solutions that provide redundancy at the routing layer and develop the Multi-Confirmation Transmission Protocol (MCTP) to take advantage of that redundancy at the transport level. The resulting system that integrates robust routing and MCTP is evaluated in experiments performed in complex environments. The integrated system is observed to provide a robust architecture that allows for near lossless communication while operating in a complex environment with less traffic than standard confirmation protocols.

ICRA Conference 2012 Conference Paper

Motion planning for robust wireless networking

Jonathan Fink
Alejandro Ribeiro
Vijay Kumar 0001

We propose an architecture and algorithms for maintaining end-to-end network connectivity for autonomous teams of robots. By adopting stochastic models of point-to-point wireless communication and computing robust solutions to the network routing problem, we ensure reliable connectivity during robot movement in complex environments. We fully integrate the solution to network routing with the choice of node positions through the use of randomized motion planning techniques. Experiments demonstrate that our method succeeds in navigating a complex environment while ensuring that end-to-end communication rates meet or exceed prescribed values within a target failure tolerance.

ICRA Conference 2012 Conference Paper

RSS gradient-assisted frontier exploration and radio source localization

Jeffrey N. Twigg
Jonathan Fink
Paul L. Yu
Brian M. Sadler

We consider the combined problem of frontier exploration in a complex indoor environment while seeking a radio source. To do this in an efficient manner, we incorporate radio signal strength (RSS) information into the exploration algorithm by locally sampling the RSS and estimating the 2-D RSS gradient. The algorithm exploits the local motion to collect RSS samples for gradient estimation and seeks to explore in a way that brings the robot to the signal source. This strategy avoids random or exhaustive exploration. An indoor experiment demonstrates the exploration algorithm that uses this information to dynamically prioritize candidate frontiers and traverse to a radio source. Simulations, including radio propagation modeling with a ray-tracing algorithm, enable study of control algorithm tradeoffs and statistical performance.

IROS Conference 2011 Conference Paper

Localization using ambiguous bearings from radio signal strength

Jason C. Derenick
Jonathan Fink
Vijay Kumar 0001

This paper presents the locomotion approach of a novel quadruped robot which is able to carry various effectors for achieving manufacturing tasks in large workspaces. Equipped with lockers on some of the passive joints and clamping devices at the end of its limbs, this quadruped uses eight actuators for achieving manufacturing tasks as well as locomotion tasks. In the following sections, we first present the proposed robot and its two working modes. Then, the locking strategy of the robot is formulated as an optimization problem. Also, a practical method for managing the limbs swinging movement is addressed. At last, the presented approach is applied on two concrete examples. Possessing a low degree of kinematic redundancy, the proposed quadruped shows a reasonable locomotion capacity which allows it to achieve locomotion with respect to some extra constrains in its workspaces.

ICRA Conference 2010 Conference Paper

Circulation of curves using vector fields: Actual robot experiments in 2D and 3D workspaces

Vinicius Mariano Gonçalves
Luciano C. A. Pimenta
Carlos Andrey Maia
Guilherme A. S. Pereira
Bruno C. O. Dutra
Nathan Michael
Jonathan Fink
Vijay Kumar 0001

Different robotic tasks can be solved by controlling a robot to circulate along curves. These include, for example, border inspection and surveillance, multirobot manipulation, and pattern generation. In a previous, work we have proposed a vector field approach for robot convergence and circulation along time-varying curves embedded in N-dimensional spaces. In the present work we instantiate this approach for three-dimensional spaces and, for the first time, show the efficacy of this method to control actual robots. Besides new theoretical analysis when constant speed control is applied, we present experimental results with aerial (quadrotors) and ground (differential-driven) robot.

ICRA Conference 2010 Conference Paper

Online methods for radio signal mapping with mobile robots

Jonathan Fink
Vijay Kumar 0001

In this paper we explore methods for the online mapping of received radio signal strength with mobile robots and localizing the source of the radio signal. By utilizing Gaussian processes, we are able to build an online model of the signal-strength map that can, in turn, be used to provide the current maximum likelihood estimate of the source location. Furthermore, using the estimate of the source location, the Gaussian process model allows for prediction of received signal strength with confidence bounds in regions of the environment that have not been explored. Finally, we develop a control law for collecting samples of the signal strength with mobile robots that allows for online estimation of the radio signal source.

IROS Conference 2009 Conference Paper

Experimental characterization of radio signal propagation in indoor environments with application to estimation and control

Jonathan Fink
Nathan Michael
Aleksandr Kushleyev
Vijay Kumar 0001

We study radio signal propagation in indoor environments using low-power devices leveraging the Zigbee and Bluetooth specifications. We present results from experiments where two robots equipped with radio signal devices and enabled to control and localize autonomously in an indoor hallway and laboratory environment densely sample RSSI at various times over several days. We show that simulated RSSI measurements using existing radio signal models and experimentally gathered RSSI measurements match closely, suggesting that for robotics applications requiring predicted RSSI, low-power radio signal devices are a well-posed sensing modality.

ICRA Conference 2008 Conference Paper

Meso-scale manipulation: System, modeling, planning and control

David J. Cappelleri
Peng Cheng 0009
Jonathan Fink
Bogdan Gavrea
Vijay Kumar 0001

Manipulation and assembly tasks are typically characterized by many nominally rigid bodies coming into frictional contacts, possibly involving impacts. Manipulation tasks are difficult to model because uncertainties associated with friction and assembly tasks are particularly hard to analyze because of the interplay between process tolerance and geometric uncertainties due to manufacturing errors. Manipulation at the meso (hundred microns to millimeters) and micro (several microns to tens of microns) scale is even harder for several reasons. It is difficult to measure forces at the micro-netwon level reliably using off-the-shelf force sensors and good force-feedback control schemes have not proved successful. It is hard to manufacture general-purpose end effectors at this scale and it is even more difficult to grasp and manipulate parts at the micro and meso level than it is at the macro level. Finally, the lack of good models of the mechanics of contact interactions at this scale means that model-based approaches to planning and control are difficult.

ICRA Conference 2008 Conference Paper

Multi-robot manipulation via caging in environments with obstacles

Jonathan Fink
M. Ani Hsieh
Vijay Kumar 0001

We present a decentralized approach to multirobot manipulation where the team of robots surround and trap an object and transport it, by dragging or pushing, to the goal configuration in an environment with obstacles. The proposed feedback controllers are obtained by sequentially composing vector fields or behaviors and are decentralized in the sense that robots do not exchange each other’s state information. Rather, cooperative manipulation is achieved by relying solely on each robot’s local information and a global knowledge of the task. We present computer simulations and experimental results obtained using our multi-robot testbed.

IROS Conference 2007 Conference Paper

Controlling a team of ground robots via an aerial robot

Nathan Michael
Jonathan Fink
Vijay Kumar 0001

We consider the task of controlling a large team of nonholonomic ground robots with an unmanned aerial vehicle in a decentralized manner that is invariant to the number of ground robots. The central idea is the development of an abstraction for the team of ground robots that allows the aerial platform to control the team without any knowledge of the specificity of individual vehicles. This happens in much the same way as a human operator can control a single robot vehicle by simply commanding the forward and turning velocities without a detailed knowledge of the specifics of the robot. The abstraction includes a gross model of the shape of the formation of the team and information about the position and orientation of the team in the plane. We derive controllers that allow the team of robots to move in formation while avoiding collisions and respecting the abstraction commanded by the aerial platform. We provide simulation and experimental results using a team of indoor mobile robots and a three-dimensional, cable-controlled, parallel robot which serves as our indoor unmanned aerial platform.

ICRA Conference 2007 Conference Paper

daVinci Code: A Multi-Model Simulation and Analysis Tool for Multi-Body Systems

Stephen Berard
Jeffrey C. Trinkle
Binh Nguyen 0002
Ben Roghani
Jonathan Fink
Vijay Kumar 0001

This paper discusses the design and current capabilities of a new software tool, dVC, capable of simulating planar systems of bodies experiencing unilateral contacts with friction. Since different problems require different levels of accuracy, dVC provides user-selectable body types (rigid or locally-compliant), motion models (first-order, quasi-static, dynamic), and several state-of-the-art time-stepping methods. One can also choose to include friction between each body and the plane of motion. To support optimal and robust part design, dVC also allows on-the-fly changes to parameters of the geometric and physical models. The results obtained for three representative planar problems are presented: the design of a passive part-orienting device, the planning of a mesoscale assembly operation, and the design of a grasp strategy.

ICRA Conference 2006 Conference Paper

Designing Open-loop Plans for Planar Micro-manipulation

David J. Cappelleri
Jonathan Fink
Barry Munkundakrisnam
Vijay Kumar 0001
Jeffrey C. Trinkle

This paper describes a test-bed for planar micro manipulation tasks and a framework for planning based on quasi-static models of mechanical systems with frictional contacts. We show how planar peg-in-the-hole assembly tasks can be designed using randomized motion planning techniques with Mason's models for quasi-static manipulation. Finally, we present simulation and experimental results in support of our methodology