Author name cluster

Nils Napp

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

2 author rows

ICRA Conference 2025 Conference Paper

Improved Bag-of-Words Image Retrieval with Geometric Constraints for Ground Texture Localization

Aaron Wilhelm
Nils Napp

Ground texture localization using a downward-facing camera offers a low-cost, high-precision localization solution that is robust to dynamic environments and requires no environmental modification. We present a significantly improved bag-of-words (BoW) image retrieval system for ground texture localization, achieving substantially higher accuracy for global localization and higher precision and recall for loop closure detection in SLAM. Our approach leverages an approximate $k$ -means (AKM) vocabulary with soft assignment, and exploits the consistent orientation and constant scale constraints inherent to ground texture localization. Identifying the different needs of global localization vs. loop closure detection for SLAM, we present both high-accuracy and high-speed versions of our algorithm. We test the effect of each of our proposed improvements through an ablation study and demonstrate our method's effectiveness for both global localization and loop closure detection. With numerous ground texture localization systems already using BoW, our method can readily replace other generic BoW systems in their pipeline and immediately improve their results.

ICRA Conference 2025 Conference Paper

Monotone Subsystem Decomposition for Efficient Multi-Objective Robot Design

Andrew Wilhelm
Nils Napp

Automating design minimizes errors, accelerates the design process, and reduces cost. However, automating robot design is challenging due to recursive constraints, multiple design objectives, and cross-domain design complexity possibly spanning multiple abstraction layers. Here we look at the problem of component selection, a combinatorial optimization problem in which a designer, given a robot model, must select compatible components from an extensive catalog. The goal is to satisfy high-level task specifications while optimally balancing trade-offs between competing design objectives. In this paper, we extend our previous constraint programming approach to multi-objective design problems and propose the novel technique of monotone subsystem decomposition to efficiently compute a Pareto front of solutions for large-scale problems. We prove that subsystems can be optimized for their Pareto fronts and, under certain conditions, these results can be used to determine a globally optimal Pareto front. Furthermore, subsystems serve as an intuitive design abstraction and can be reused across various design problems. Using an example quadcopter design problem, we compare our method to a linear programming approach and demonstrate our method scales better for large catalogs, solving a multi-objective problem of 10 25 component combinations in seconds. We then expand the original problem and solve a task-oriented, multi-objective design problem to build a fleet of quadcopters to deliver packages. We compute a Pareto front of solutions in seconds where each solution contains an optimal component-level design and an optimal package delivery schedule for each quadcopter.

ICRA Conference 2025 Conference Paper

Robotic Dry-Stacking of Clocháin with Irregular Stones

Yifang Liu
Nils Napp

This paper explores automated robotic construction of clocháin 2, a type of corbelled rock shelter, traditionally crafted by skilled workers. While robots have been employed for simple dry-stacking tasks in the past, such as construction of stone walls or vertical stone towers, the question of whether robots possess the capacity to construct more functional structures remains unanswered. This study presents a significant step forward in robotic dry-stacking of functional structures: the assembly of natural stones into freestanding clocháin structures. We also present a set of stackability measures to aid stone selection, which significantly improves the stability of the planned structures. Our sequential filtering approach, originally designed for planning stone walls, plays a foundational role in achieving stable clochán construction. Experimental results validate the effectiveness of the stackability measures and demonstrate the physical execution of dry-stacking clocháin, The progress demonstrated in this paper opens the door to robotic construction of a wide range of utility structures in unstructured environments.

IROS Conference 2025 Conference Paper

Robust Robotic Assembly of Reusable, Rectangular Blocks

Zhongming Huang
Hongyu Yao
Haocheng Peng
Shih-Ming Lin
Kirstin Petersen
Nils Napp

This paper investigates the importance and design implications for use of rectangular blocks in collective robotic construction systems with distributed control. Specifically, we introduce an automated solver for optimizing the overlaps in user-specified structures; a new robot design capable of manipulating, fastening, and climbing over blocks as wide as the robot; detailed analysis of robot primitives and demonstration of rectilinear, curved, cantilever, and corbeled arch structures; and results from a physics simulator showing how overlaps improve structural integrity when the depositions are noisy. This work represents an important step towards efficient and versatile large-scale robotic construction.

IROS Conference 2024 Conference Paper

Frozen Assets: Leveraging Ice, Water, and Phase Transitions in Robots

Aaron Wilhelm
Andrew Wilhelm
Lydia Isabela Calderon-Aceituno
Nils Napp
Kirstin Petersen
E. Farrell Helbling

Robots are especially useful in cold, remote, and inhospitable environments such as polar regions and extraterrestrial settings. Due to subfreezing temperatures and limited resources in these environments, robots made of ice are particularly advantageous. In this paper we demonstrate how the solid and liquid phases of water, and transitions between these phases, can be leveraged into common robot designs for modular robots, robot arms, rovers, and soft robots. We explore how robots can utilize structural elements made of ice and exploit the phase change between ice and water to augment their capabilities. Additionally, we do a scaling analysis of ice structural elements to provide insight on their performance at different length scales and ambient temperatures.

ICRA Conference 2024 Conference Paper

Inexpensive, Automated Pruning Weight Estimation in Vineyards

Jonathan Jaramillo
Aaron Wilhelm
Nils Napp
Justine E. Vanden Heuvel
Kirstin Petersen

Pruning weight is indicative of a vine’s ability to produce a crop the following year, informing vineyard management. Current methods for estimating pruning weight are costly, laborious, and/or require specialized know-how and equipment. In this paper we demonstrate an affordable, simple, computer vision-based method to measure pruning weight using a smartphone camera and structured light which produces results better than state-of-the-art techniques for vertical shoot position (VSP) vines and demonstrate initial steps towards estimating pruning weight in high cordon procumbent (HC) vines such as Concord. The simplicity and affordability of this technique lends its self to deployment by farmers today or on future viticulture robotics platforms. We achieved an R2=. 80 for VSP vines (better than state-of-the-art computer vision-based methods) and R2=. 29 for HC vines (not previously attempted with computer vision-based methods).

ICRA Conference 2024 Conference Paper

Lightweight Ground Texture Localization

Aaron Wilhelm
Nils Napp

We present a lightweight ground texture based localization algorithm (L-GROUT) that improves the state of the art in performance and can be run in real-time on single board computers without GPU acceleration. Such computers are ubiquitous on small indoor robots and thus this work enables high-precision, millimeter-level localization without instrumenting, marking, or modifying the environment. The key innovations are an improved database feature extraction algorithm, a dimensionality reduction method based on locality preserving projections (LPP) that can accommodate faster-to-compute binary features, and an improved spatial filtering step that better preserves performance when the databases are tuned for lightweight applications. We demonstrate the approach by running the whole system on a low-cost single board computer (Raspberry Pi 4) to produce global localization estimates at greater than 4Hz on an outdoor asphalt dataset.

IROS Conference 2023 Conference Paper

Constraint Programming for Component-Level Robot Design

Andrew Wilhelm
Nils Napp

Effective design automation for building robots would make development faster and easier while also less prone to design errors. However, complex multi-domain constraints make creating such tools difficult. One persistent challenge in achieving this goal of design automation is the fundamental problem of component selection, an optimization problem where, given a general robot model, components must be selected from a possibly large set of catalogs to minimize design objectives while meeting target specifications. Different approaches to this problem have used Monotone Co-Design Problems (MCDPs) or linear and quadratic programming, but these require judicious system approximations that affect the accuracy of the solution. We take an alternative approach formulating the component selection problem as a combinatorial optimization problem, which does not require any system approximations, and using constraint programming (CP) to solve this problem with a depth-first branch-and-bound algorithm. As the efficacy of CP critically depends upon the orderings of variables and their domain values, we present two heuristics specific to the problem of component selection that significantly improve solve time compared to traditional constraint satisfaction programming heuristics. We also add redundant constraints to the optimization problem to further improve run time by evaluating certain global constraints before all relevant variables are assigned. We demonstrate that our CP approach can find optimal solutions from over 20 trillion candidate solutions in only seconds, up to 48 times faster than an MCDP approach solving the same problem. Finally, for three different robot designs we build the corresponding robots to physically validate that the selected components meet the target design specifications.

ICRA Conference 2020 Conference Paper

Autonomous Modification of Unstructured Environments with Found Material

Vivek Thangavelu
Maíra Saboia da Silva
Jiwon Choi
Nils Napp

The ability to autonomously modify their environment dramatically increases the capability of robots to operate in unstructured environments. We develop a specialized construction algorithm and robotic system that can autonomously build motion support structures with previously unseen objects. The approach is based on our prior work on adaptive ramp building algorithms, but it eliminates the assumption of having specialized building materials that simplify manipulation and planning for stability. Utilizing irregularly shaped stones makes the problem significantly more challenging since the outcome of individual placements is sensitive to details of contact geometry and friction, which are difficult to observe. To reuse the same high-level algorithm, we develop a new physics-based planner that explicitly considers the uncertainty produced by incomplete in-situ sensing and imprecision during pickup and placement. We demonstrate the approach on a robotic system that uses a newly developed gripper to reliably pick up stones with minimal additional sensors or complex grasp planning. The resulting system can build structures with more than 70 stones, which in turn provide traversable paths to previously inaccessible locations.

ICRA Conference 2019 Conference Paper

Approximate Stability Analysis for Drystacked Structures

Yifang Liu
Maíra Saboia da Silva
Vivek Thangavelu
Nils Napp

We introduce a fast approximate stability analysis into an automated dry stacking procedure. Evaluating structural stability is essential for any type of construction, but especially challenging in techniques where building elements remain distinct and do not use fasteners or adhesives. Due to the irregular shape of construction materials, autonomous agents have restricted knowledge of contact geometry, which makes existing analysis tools difficult to deploy. In this paper, a geometric safety factor called kern is used to estimate how much the contact interface can shrink and the structure still be feasible, where feasibility can be checked efficiently using linear programming. We validate the stability measure by comparing the proposed methods with a fully simulated shaking test in 2D. We also improve existing heuristics-based planning by adding the proposed measure into the assembly process.

IROS Conference 2018 Conference Paper

Deep Q-Learning for Dry Stacking Irregular Objects

Yifang Liu
Seyed Mahdi Shamsi
Le Fang 0002
Changyou Chen
Nils Napp

We propose a reinforcement learning approach for automatically building dry stacked (i. e. no mortar) structures with irregular objects. Stacking irregular objects is a challenging problem since each assembly action can be drawn from a continuous space of poses for an object, and several local geometric and physical considerations strongly affect the stability. To tackle this challenge, we concentrate on a simplified 2D version of the problem. We present a reinforcement learning algorithm based on deep Q-learning, where the learned Q-function, which maps state-action pairs into expected long-term rewards, is represented by a deep neural network. As the action space is continuous the Q-network is trained by sampling a finite number of actions that consider both geometric and physical constraints to approximate the target Q-values, Experiments show that the proposed method outperforms previous heuristics-based planning, leading to super construction with objects containing a significant amount of variations. We validate the generated stacking plans by executing them using a robot arm and manufactured, irregular objects.

ICRA Conference 2018 Conference Paper

Dry Stacking for Automated Construction with Irregular Objects

Vivek Thangavelu
Yifang Liu
Maíra Saboia da Silva
Nils Napp

We describe a method for automatically building structures from stacked, irregularly shaped objects. This is a simplified model for the problem of building dry stacked structures (i. e. no mortar) from found stones. Although automating such construction methods would be ideally suited for disaster areas or remote environments, currently such structures need to be built by skilled masons. No practical methods for automating the assembly planning process are known. The problem is challenging since each assembly action can be drawn from a continuous space poses for an object and several local geometric and physical considerations strongly affect the overall stability. We show that structures that are built following a stacking order for perfect bricks can accommodate a limited amount of irregularity, however, their performance degrades quickly when objects deviate from their ideal shape. We present a strategy for stacking irregular shapes that first considers geometric and physical constraints to find a small set of feasible actions and then further refines this set by using heuristics gathered from instructional literature for masons. The proposed method of choosing assembly actions allows construction with objects that contain a significant amount of variation.

ICRA Conference 2014 Conference Paper

Robotic construction of arbitrary shapes with amorphous materials

Nils Napp
Radhika Nagpal

We present a locally reactive algorithm to construct arbitrary shapes with amorphous materials. The goal is to provide methods for robust robotic construction in unstructured, cluttered terrain, where deliberative approaches with pre-fabricated construction elements are difficult to apply. Amorphous materials provide a simple way to interface with existing obstacles, as well as irregularly shaped previous depositions. The local reactive nature of these algorithms allows robots to recover from disturbances, operate in dynamic environments, and provides a way to work with scalable robot teams.

ICRA Conference 2014 Conference Paper

Simple passive valves for addressable pneumatic actuation

Nils Napp
Brandon Araki
Michael T. Tolley
Radhika Nagpal
Robert J. Wood

We present a method for setting the pressure of multiple chambers using a single pressure source when they are interconnected via band-pass valves. These valves can be constructed from simple passive devices that behave like leaky check valves. We present the theory of operation and design parameters for individual valves, give a control strategy for serial connections of pressure chambers, and demonstrate the approach by building prototype valves and using them to control serially connected soft-robotic actuators from a single pressure source.

NeurIPS Conference 2013 Conference Paper

Message Passing Inference with Chemical Reaction Networks

Nils Napp
Ryan Adams

Recent work on molecular programming has explored new possibilities for computational abstractions with biomolecules, including logic gates, neural networks, and linear systems. In the future such abstractions might enable nanoscale devices that can sense and control the world at a molecular scale. Just as in macroscale robotics, it is critical that such devices can learn about their environment and reason under uncertainty. At this small scale, systems are typically modeled as chemical reaction networks. In this work, we develop a procedure that can take arbitrary probabilistic graphical models, represented as factor graphs over discrete random variables, and compile them into chemical reaction networks that implement inference. In particular, we show that marginalization based on sum-product message passing can be implemented in terms of reactions between chemical species whose concentrations represent probabilities. We show algebraically that the steady state concentration of these species correspond to the marginal distributions of the random variables in the graph and validate the results in simulations. As with standard sum-product inference, this procedure yields exact results for tree-structured graphs, and approximate solutions for loopy graphs.

IROS Conference 2012 Conference Paper

Materials and mechanisms for amorphous robotic construction

Nils Napp
Olive R. Rappoli
Jessica M. Wu
Radhika Nagpal

We present and compare three different amorphous materials for robotic construction. By conforming to surfaces they are deposited on, such materials allow robots to reliably construct in unstructured terrain. However, using amorphous materials presents a challenge to robotic manipulation. We demonstrate how deposition of each material can be automated and compare their material properties, cost, and cost in time in order to evaluate their suitability for developing amorphous robotic construction system.

ICRA Conference 2011 Conference Paper

Load balancing for multi-robot construction

Nils Napp
Eric Klavins

In distributed multi-robot construction it is important to set the relative rates at which different construction sites receive raw building materials. Otherwise, subtasks finish at different times introducing unnecessary delays. We present a feedback algorithm to achieve robust load balancing in routing building materials for stochastic, distributed, multi-robot construction systems. We express global behavior in terms of local reactive behavior via Guarded Command Programming with Rates and prove correctness of the load-balancing controller for a wide range of conditions. We adapt a proof from earlier work on controlling Stochastic Chemical Kinetic systems and illustrate the algorithm on the Factory-Floor robotic testbed [1].

ICRA Conference 2010 Conference Paper

Robust by composition: Programs for multi-robot systems

Nils Napp
Eric Klavins

This paper describes how to specify the local reactive behavior of robots via guarded command programs with rates. These programs express concurrency and can be composed easily. Rates allow programs to be interpreted as Markov processes, which we use to define an appropriate notion of robustness and performance. We use composition to “robustify” programs with good performance, i. e. create a robust program with good performance from a program that has good performance but is not robust. We demonstrate this approach on a sub process of a reconfiguration program in a multi-robot system.

ICRA Conference 2006 Conference Paper

The Statistical Dynamics of Programmed Self-assembly

Nils Napp
Samuel A. Burden
Eric Klavins

We describe how a graph grammar program for robotic self-assembly, together with measurements of kinetic rate data yield a Markov process model of the dynamics of programmed self-assembly. We demonstrate and validate the method by applying it to a physical testbed consisting of a number of "programmable parts", which are able to control their local interactions according to their on-board programs. We describe a technique for obtaining kinetic rate constants from simulation and a comparison of the behavior predicted by the Markov model with the behavior predicted by a high-fidelity simulation of the system

IROS Conference 2005 Conference Paper

Programmable parts: a demonstration of the grammatical approach to self-organization

Joshua D. Bishop
Samuel A. Burden
Eric Klavins
R. Kreisberg
W. Malone
Nils Napp
T. Nguyen

In this paper, we introduce a robotic implementation of the theory of graph grammars (Klavins et al. , 2005), which we use to model and direct self-organization in a formal, predictable and provably-correct fashion. The robots, which we call programmable parts, float passively on an air table and bind to each other upon random collisions. Once attached, they execute local rules that determine how their internal states change and whether they should remain bound. We demonstrate through experiments how they can self-organize into a global structure by executing a common graph grammar in a completely distributed fashion. The system also presents a challenge to the grammatical method (and to distributed systems approaches in general) due to the stochastic nature of its dynamics. We conclude by discussing these challenges and our initial approach to addressing them.