Author name cluster

Ross L. Hatton

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.

21 papers

1 author row

ICRA Conference 2025 Conference Paper

Geometric Design and Gait Co-Optimization for Soft Continuum Robots Swimming at Low and High Reynolds Numbers

Yanhao Yang
Ross L. Hatton

Recent advancements in soft actuators have enabled soft continuum swimming robots to achieve higher efficiency and more closely mimic the behaviors of real marine animals. However, optimizing the design and control of these soft continuum robots remains a significant challenge. In this paper, we present a practical framework for the co-optimization of the design and control of soft continuum robots, approached from a geometric locomotion analysis perspective. This framework is based on the principles of geometric mechanics, accounting for swimming at both low and high Reynolds numbers. By generalizing geometric principles to continuum bodies, we achieve efficient geometric variational co-optimization of designs and gaits across different power consumption metrics and swimming environments. The resulting optimal designs and gaits exhibit greater efficiencies at both low and high Reynolds numbers compared to three-link or serpenoid swimmers with the same degrees of freedom, approaching or even surpassing the efficiencies of infinitely flexible swimmers and those with higher degrees of freedom.

ICRA Conference 2024 Conference Paper

Towards Geometric Motion Planning for High-Dimensional Systems: Gait-Based Coordinate Optimization and Local Metrics

Yanhao Yang
Capprin Bass
Ross L. Hatton

Geometric motion planning offers effective and interpretable gait analysis and optimization tools for locomoting systems. However, due to the curse of dimensionality in coordinate optimization, a key component of geometric motion planning, it is almost infeasible to apply current geometric motion planning to high-dimensional systems. In this paper, we propose a gait-based coordinate optimization method that overcomes the curse of dimensionality. We also identify a unified geometric representation of locomotion by generalizing various nonholonomic constraints into local metrics. By combining these two approaches, we take a step towards geometric motion planning for high-dimensional systems. We test our method in two classes of high-dimensional systems - low Reynolds number swimmers and free-falling Cassie - with up to 11-dimensional shape variables. The resulting optimal gait in the high-dimensional system shows better efficiency compared to that of the reduced-order model. Furthermore, we provide a geometric optimality interpretation of the optimal gait.

IROS Conference 2023 Conference Paper

Geometric Gait Optimization for Inertia-Dominated Systems with Nonzero Net Momentum

Yanhao Yang
Ross L. Hatton

Inertia-dominated mechanical systems can achieve net displacement by 1) periodically changing their shape (known as kinematic gait) and 2) adjusting their inertia distribution to utilize the existing nonzero net momentum (known as momentum gait). Therefore, finding the gait that most effectively utilizes the two types of locomotion in terms of the magnitude of the net momentum is a significant topic in the study of locomotion. For kinematic locomotion with zero net momentum, the geometry of optimal gaits is expressed as the equilibria of system constraint curvature flux through the surface bounded by the gait, and the cost associated with executing the gait in the metric space. In this paper, we identify the geometry of optimal gaits with nonzero net momentum effects by lifting the gait description to a time-parameterized curve in shape-time space. We also propose the variational gait optimization algorithm corresponding to the lifted geometric structure, and identify two distinct patterns in the optimal motion, determined by whether or not the kinematic and momentum gaits are concentric. The examples of systems with and without fluid-added mass demonstrate that the proposed algorithm can efficiently solve forward and turning locomotion gaits in the presence of nonzero net momentum. At any given momentum and effort limit, the proposed optimal gait that takes into account both momentum and kinematic effects outperforms the reference gaits that each only considers one of these effects.

IROS Conference 2022 Conference Paper

Amoeba-inspired swimming through isoperimetric modulation of body shape

Curtis Sparks
Nathan Justus
Ross L. Hatton
Nick Gravish

In this work we present the design of a swimming robot that is inspired by the body shape modulation of small microorganisms. Amoebas are small single celled organisms that locomote through deformation and shape change of their body. To achieve similar shape modulation for swimming propulsion in a robot we developed a novel flexible appendage using tape springs. A tape spring is an elongated strip of metal with a curved cross-section that can act as a stiff structure when loaded against the curvature, while it can easily buckle when loaded with the curvature. We develop a tape spring appendage that is capable of freely deforming its perimeter through two actuation inputs. In the first portion of this paper we develop the kinematics of the appendage mechanisms and compare with experiment. Next we present the design of a surface locomoting robot that uses two appendages for propulsion. From the appendage kinematics we derive the local connection vector field for locomotion kinematics and study the optimal gait for forward swimming. Lastly, we demonstrate robot swimming performance in open water conditions. The novel appendage design in this robot is advantageous because it enables omnidirectional movement, the appendages will not tangle in debris, and they are robust to collisions and contact with structures.

ICRA Conference 2022 Conference Paper

Characterizing Error in Noncommutative Geometric Gait Analysis

Capprin Bass
Suresh Ramasamy
Ross L. Hatton

A key problem in robotic locomotion is in finding optimal shape changes to effectively displace systems through the world. Variational techniques for gait optimization require estimates of body displacement per gait cycle; however, these estimates introduce error due to unincluded high order terms. In this paper, we formulate existing estimates for displacement, and describe the contribution of low order terms to these estimates. We additionally describe the magnitude of higher (third) order effects, and identify that choice of body coordinate, gait diameter, and starting phase influence these effects. We demonstrate that variation of such parameters on two example systems (the differential drive car and Purcell swimmer) effectively manages third order contributions.

ICRA Conference 2022 Conference Paper

Enhancing Maneuverability via Gait Design

Siming Deng
Ross L. Hatton
Noah J. Cowan

The gaits of locomoting systems are typically designed to maximize some sort of efficiency, such as cost of transport or speed. Equally important is the ability to modulate such a gait to effect turning maneuvers. For drag-dominated systems, geometric mechanics provides an elegant and practical framework for both ends—gait design and gait modulation. Within this framework, “constraint curvature” maps can be used to approximate the net displacement of robotic systems over cyclic gaits. Gait optimization is made possible under a previously reported “soap-bubble” algorithm. In this work, we propose both local and global gait morphing algorithms to modify a nominal gait to provide single-parameter steering control. Using a simplified swimmer, we numerically compare the two approaches and show that for modest turns, the local approach, while suboptimal, nevertheless proves effective for steering control. A potential advantage of the local approach is that it can be readily applied to soft robots or other systems where local approximations to the constraint curvature can be garnered from data, but for which obtaining an exact global model is infeasible.

IROS Conference 2022 Conference Paper

Motion Planning for Agile Legged Locomotion using Failure Margin Constraints

Kevin Green
John Warila
Ross L. Hatton
Jonathan W. Hurst

The complex dynamics of agile robotic legged locomotion requires motion planning to intelligently adjust footstep locations. Often, bipedal footstep and motion planning use mathematically simple models such as the linear inverted pendulum, instead of dynamically-rich models that do not have closed-form solutions. We propose a real-time optimization method to plan for dynamical models that do not have closed form solutions and experience irrecoverable failure. Our method uses a data-driven approximation of the step-to-step dynamics and of a failure margin function. This failure margin function is an oriented distance function in state-action space where it describes the signed distance to success or failure. The motion planning problem is formed as a nonlinear program with constraints that enforce the approximated forward dynamics and the validity of state-action pairs. For illustration, this method is applied to create a planner for an actuated spring-loaded inverted pendulum model. In an ablation study, the failure margin constraints decreased the number of invalid solutions by between 24 and 47 percentage points across different objectives and horizon lengths. While we demonstrate the method on a canonical model of locomotion, we also discuss how this can be applied to data-driven models and full-order robot models.

IROS Conference 2022 Conference Paper

Optimal Gait Families using Lagrange Multiplier Method

Jinwoo Choi
Capprin Bass
Ross L. Hatton

The Robotic locomotion community is interested in optimal gaits for control. Based on the optimization criterion, however, there could be a number of possible optimal gaits. For example, the optimal gait for maximizing displacement with respect to cost is quite different from the maximum displacement optimal gait. Beyond these two general optimal gaits, we believe that the optimal gait should deal with various situations for high-resolution of motion planning, e. g. , steering the robot or moving in “baby steps. ” As the step size or steering ratio increases or decreases, the optimal gaits will slightly vary by the geometric relationship and they will form the families of gaits. In this paper, we explored the geometrical framework across these optimal gaits having different step sizes in the family via the Lagrange multiplier method. Based on the structure, we suggest an optimal locus generator that solves all related optimal gaits in the family instead of optimizing each gait respectively. By applying the optimal locus generator to two simplified swimmers in drag-dominated environments, we verify the behavior of the optimal locus generator.

IROS Conference 2021 Conference Paper

Geometric Motion Planning for a System on the Cylindrical Surface

Shuoqi Chen
Ruijie Fu
Ross L. Hatton
Howie Choset

Traditional geometric mechanics models used in locomotion analysis rely heavily on systems having symmetry in SE(2) (i. e. , the dynamics and constraints are invariant with respect to a system’s position and orientation) to simplify motion planning. As a result, the symmetry assumption prevents locomotion analysis on non-flat surfaces because the system dynamics may vary as a function of position and orientation. In this paper, we develop geometric motion planning strategies for a mobile system moving on a position space whose manifold structure is a cylinder: constant non-zero curvature in one dimension and zero curvature in another. To handle this non-flat position space, we adapt conventional geometric mechanics tools - in particular the system connection and the constraint curvature function - to depend on the system orientation. In addition, we introduce a novel constraint projection method to a variational gait optimizer and demonstrate how to design gaits that allow the example system to move on the cylinder with optimal efficiency.

ICRA Conference 2020 Conference Paper

Planning for the Unexpected: Explicitly Optimizing Motions for Ground Uncertainty in Running

Kevin Green
Ross L. Hatton
Jonathan W. Hurst

We propose a method to generate actuation plans for a reduced order, dynamic model of bipedal running. This method explicitly enforces robustness to ground uncertainty. The plan generated is not a fixed body trajectory that is aggressively stabilized: instead, the plan interacts with the passive dynamics of the reduced order model to create emergent robustness. The goal is to create plans for legged robots that will be robust to imperfect perception of the environment, and to work with dynamics that are too complex to optimize in real-time. Working within this dynamic model of legged locomotion, we optimize a set of disturbance cases together with the nominal case, all with linked inputs. The input linking is nontrivial due to the hybrid dynamics of the running model but our solution is effective and has analytical gradients. The optimization procedure proposed is significantly slower than a standard trajectory optimization, but results in robust gaits that reject disturbances extremely effectively without any replanning required.

ICRA Conference 2016 Conference Paper

Aiming and vaulting: Spider inspired leaping for jumping robots

Hossein Faraji
Ramsey Tachella
Ross L. Hatton

Jumping spiders are capable of targeted jumps by using their front legs to guide the release of energy from their rear legs. In this paper, we present a simplified model of the jumping spider based on the anatomy of the real spider. The immediate goal of this model is to understand how the geometry of the legs affects the jumping motion, with the further goal of using this geometry in the future development of jumping robots. Through a set of simulations, dynamic analysis, and experiments with a physical realization of our model, we identify several features of the spiders' jumping mechanism, most notably that “vaulting” with the front legs allows the system to generate flatter take-off trajectories than could be achieved by simple aiming of a spring-release mechanism.

ICRA Conference 2015 Conference Paper

Passive-dynamic leg design for agile robots

Andy Abate
Ross L. Hatton
Jonathan W. Hurst

The spring-mass locomotion paradigm is showing great promise as a template for agile and efficient robots. Efficiency and stability are enabled by the passive generation of locomotion patterns, rather than enforced by the control system. However, as leg designs develop more articulation and complexity, a problem arises: how do we implement a chosen set of passive dynamics in complex hardware? We present compliance and impact inertia analyses in a “visually tactile” way, allowing complex and redundant mechanism designs to be easily evaluated. The patterns shown here begin a framework for the comprehensive design of agile, highly dynamic robots.

ICRA Conference 2015 Conference Paper

Wrapping a target with a tethered projectile

Lucas Hill
Thomas Woodward
Hitoshi Arisumi
Ross L. Hatton

A casting manipulator is a robot that launches a payload as a projectile then alters the ballistic trajectory by pulling on an attached tether. Prior work in casting manipulation has focused on applying impulses through the tether to place the payload at a specific location and then retract it. In the spirit of whole-body and whole-arm manipulation, we propose that the tether itself can be used to act on the environment, rather than serving only as a means of directing the projectile. As a first step in this direction, we consider the case of throwing an end-weighted line to wrap a target above and away from the launch point. We explore the necessary conditions for successfully wrapping a target, including the various types of wrapping and the conditions required to make these wraps.

IROS Conference 2014 Conference Paper

Nonlinear dimensionality reduction for kinematic cartography with an application toward robotic locomotion

Tony Dear
Ross L. Hatton
Howie Choset

Planning robot motions often requires a notion of the “distance” between configurations or the “length” of a trajectory connecting them in the configuration space. If these quantities are defined so as to correspond to the effort required to change configurations, then they would likely differ from the Euclidean distance or arclength in the system's configuration parameters, distorting the visual representation of the relative costs of executing the motions. This problem is fundamentally similar to that of producing map projections with minimal distortion in cartography. A separate problem is that of nonlinear dimensionality reduction (NLDR), which, given a set of data, projects it into a lower-dimensional space while seeking to retain the geometric relationship between data points. In this paper, we show that NLDR can be applied to the kinematic cartography problem, allowing us to generate system parameterizations in which distance and arclength correspond to the effort of motion.

ICRA Conference 2013 Conference Paper

Snakes on a plan: Toward combining planning and control

Ross L. Hatton
Ross A. Knepper
Howie Choset
David Rollinson
Chaohui Gong
Enric Galceran

Highly articulated robot locomotion systems, such as snake robots, present special motion planning challenges. They possess many degrees of freedom, and therefore are modeled by a high dimensional configuration space which must be searched to plan a path. Kinematic and dynamic constraints further complicate the selection of effective controls. Finally, snake robots often have multiple modes of interaction with the terrain as contacts are made and broken, leading to complex and imperfect motion models. We believe that the space of useful controls that provides desirable motions, however, is much smaller. Useful net motions for such systems are often generated via gaits, or cyclic motions in the shape space. Gaits transform a high-dimensional continuum search into a relatively tractable discrete search. In this paper, we put forward a framework which allows a planner to generate paths in a low dimensional work space and select among gaits, pre-planned motions in the robot's shape space. The contribution of this paper rests on the “virtual chassis” which is a choice of body frame for the snake robot that allows the planner to efficiently select among and plan with gaits to direct the robot along the work space path. We demonstrate this planner running on a simulated snake robot navigating through a variety of clutter scenarios. The virtual chassis also has the benefit of allowing us to generalize notions of controllability to gait motions.

ICRA Conference 2012 Conference Paper

Conical sidewinding

Chaohui Gong
Ross L. Hatton
Howie Choset

Sidewinding is an efficient translation gait used by snakes and snake robots over flat ground, and resembles a helical tread moving over a core cylindrical geometry. Most sidewinding research has focused on straight-line translation of the snake, and less on steering capabilities. Here, we offer a new, geometrically intuitive method for steering this gait: Tapering the core cylinder into a cone, such that one end moves faster than the other, changing the heading of the robot as it drives forward. We present several design tools for working with this cone, along with experimental results on a physical robot turning at different rates.

IROS Conference 2011 Conference Paper

Geometric maneuverability with applications to low reynolds number swimming

Ross L. Hatton
Lisa J. Burton
Anette E. Hosoi
Howie Choset

A mobile system's maneuverability describes the scale and span of the velocities with which it can move. In this paper, we present a new geometric framework for describing the maneuverability of kinematic locomoting systems, inspired by the manipulability analysis of robotic arms. This framework describes both the local maneuverability in the neighborhood of each shape the system can assume and the cyclic maneuverability achieved by executing gaits from a library. Additionally, the gait-level analysis includes tools that direct the search for gaits whose inclusion into the library will usefully improve the maneuverability. Throughout, we provide examples based on a swimming system operating at low Reynolds number.

ICRA Conference 2010 Conference Paper

Optimizing coordinate choice for locomoting systems

Ross L. Hatton
Howie Choset

Gait evaluation techniques that use Stokes's theorem to integrate a system's equations of motion have traditionally been limited to finding only the net rotations or small translations produced by gaits. Recently, we have observed that certain choices of generalized coordinates allow these techniques to be extended to gaits that produce large translations. In this paper, we present a method for finding the optimal coordinate choice for this purpose, based on a Hodge-Helmholtz decomposition of the system constraints, and demonstrate the efficacy of the Stokes's theorem approach over a wide variety of gaits when using the optimized coordinate choice.

ICRA Conference 2010 Conference Paper

Sidewinding on slopes

Ross L. Hatton
Howie Choset

Sidewinding is an efficient translation gait used by snakes over flat ground. When implemented on snake robots, it retains its general effectiveness, but becomes unstable on sloped surfaces. Flattening the sidewinding motion along the surface to provide a more stable base corrects for this instability, but degrades other performance characteristics, such as efficiency and handling of rough terrain. In this paper, we identify stability conditions for a sidewinder on a slope and find a solution for the minimum aspect ratio of the sidewinding pattern needed to maintain stability. Our theoretical results are supported by experiments on snake robots. In constructing our stability analysis, we present a new, tread-based model for sidewinding that is both consistent with previous models and provides new intuition regarding the kinematics of the gait. This new interpretation of sidewinding further admits a symmetry-based model reduction that simplifies its analysis. Additionally, an intermediate stage of the theoretical work contains a comprehensive analysis of the behavior of an ellipse in rolling contact with a sloped surface.

IROS Conference 2009 Conference Paper

Generating gaits for snake robots by annealed chain fitting and Keyframe wave extraction

Ross L. Hatton
Howie Choset

Snake robots have many degrees of freedom, which makes them both extremely versatile and complex to control. In this paper, we address this complexity by introducing two algorithms. Annealed chain fitting efficiently maps a continuous backbone curve to a set of joint angles for a snake robot. Keyframe wave extraction takes joint angles fit to a sequence of backbone curves, and identifies parameterized periodic functions which produce those sequences. Together, they allow a designer to conceive a gait in terms three-dimensional shapes and translate them into easily manipulated wave functions. We validate the algorithms by using them to produce rolling gaits for crawling and climbing.

IROS Conference 2007 Conference Paper

Design of a modular snake robot

Cornell Wright III
Aaron M. Johnson 0001
Aaron Peck
Zachary McCord
Allison Naaktgeboren
Philip Gianfortoni
Manuel González-Rivero
Ross L. Hatton

Many factors such as size, power, and weight constrain the design of modular snake robots. Meeting these constraints requires implementing a complex mechanical and electrical architecture. Here we present our solution, which involves the construction of sixteen aluminum modules and creation of the Super Servo, a modified hobby servo. To create the Super Servo, we have replaced the electronics in a hobby servo, adding such components as sensors to monitor current and temperature, a communications bus, and a programmable microcontroller. Any robust solution must also protect components from hazardous environments such as sand and brush. To resolve this problem we insert the robots into skins that cover their surface. Functions such as climbing the inside and outside of a pipe add a new dimension of interaction. Thus we attach a compliant, high-friction material to every module, which assists in tasks that require gripping. This combination of the mechanical and electrical architectures results in a robust and versatile robot.