About

Louis Whitcomb is a professor of mechanical engineering at Johns Hopkins University, with a secondary appointment in the Department of Computer Science. He is renowned for his innovative robotics research and development in space, underwater, and other extreme environments, as well as for developing novel systems for medicine and industry. Whitcomb founded and directs the Johns Hopkins Dynamical Systems and Control Laboratory (DSCL), leading student researchers in nonlinear and adaptive control of robot systems, robot actuators and sensors, mechanical design, and control systems design for high-performance robot control. His lab has participated in the development of underwater vehicles for oceanographic science missions, including the Nereus hybrid underwater vehicle that dove to the bottom of the Mariana Trench and the Nereid Under-Ice (NUI) hybrid underwater vehicle deployed under Arctic sea ice in 2014, 2016, and 2019. Whitcomb was co-PI on these vehicle development projects with collaborators at the Woods Hole Oceanographic Institution (WHOI). He has extensive experience from more than 25 oceanographic expeditions and sea-trials. Additionally, he develops manipulators for medical robotic arms to improve control algorithms, enable dexterous surgical tasks, and enhance upper-limb prostheses. Whitcomb served as chair of the Department of Mechanical Engineering from 2013 to 2017 and is the director of the Master of Science in Engineering program for robotics. He was the founding director of the Laboratory for Computational Sensing and Robotics (LCSR) from 2007 to 2013 and currently serves as its deputy director. An adjunct scientist with WHOI since 1995, Whitcomb has also worked as a research and development engineer with GMFanuc Robotics Corporation and completed post-doctoral fellowships at the University of Tokyo and WHOI. He holds 15 patents and is a sought-after consultant in robotics, dynamics, navigation, control, and real-time control systems. Whitcomb has received numerous awards, including best-paper awards, an NSF CAREER Award, an Office of Naval Research Young Investigator Award, and was named a Fellow of IEEE in 2011 for his contributions to the field. He has been honored with multiple teaching awards and is an active member of several professional societies, frequently presenting at robotics conferences worldwide.

Research topics

• Computer science
• Engineering
• Marine engineering
• Artificial intelligence
• Geology

Selected publications

• Modeling Adaptive Tracking of Predictable Stimuli in Electric Fish

  ArXiv.org · 2025-09-18

  preprintOpen access

  The weakly electric fish \emph{Eigenmannia virescens} naturally swims back and forth to stay within a moving refuge, tracking its motion using visual and electrosensory feedback. Previous experiments show that when the refuge oscillates as a low-frequency sinusoid (below about 0.5 Hz), the tracking is nearly perfect, but phase lag increases and gain decreases at higher frequencies. Here, we model this nonlinear behavior as an adaptive internal model principle (IMP) system. Specifically, an adaptive state estimator identifies the \emph{a priori} unknown frequency, and feeds this parameter estimate into a closed-loop IMP-based system built around a lightly damped harmonic oscillator. We prove that the closed-loop tracking error of the IMP-based system, where the online adaptive frequency estimate is used as a surrogate for the unknown frequency, converges exponentially to that of an ideal control system with perfect information about the stimulus. Simulations further show that our model reproduces the fish refuge tracking Bode plot across a wide frequency range. These results establish the theoretical validity of combining the IMP with an adaptive identification process and provide a basic framework in adaptive sensorimotor control.

  PublisherOA PDFDOI

• Modeling Adaptive Tracking of Predictable Stimuli in Electric Fish

  IEEE Control Systems Letters · 2025-01-01

  article

  The weakly electric fish Eigenmannia virescens naturally swims back and forth to stay within a moving refuge, tracking its motion using visual and electrosensory feedback. Previous experiments show that when the refuge oscillates as a low-frequency sinusoid (below about 0.5 Hz), the tracking is nearly perfect, but phase lag increases and gain decreases at higher frequencies. Here, we model this nonlinear behavior as an adaptive internal model principle (IMP) system. Specifically, an adaptive state estimator identifies the a priori unknown frequency, and feeds this parameter estimate into a closed-loop IMP-based system built around a lightly damped harmonic oscillator. We prove that the closed-loop tracking error of the IMP-based system, where the online adaptive frequency estimate is used as a surrogate for the unknown frequency, converges exponentially to that of an ideal control system with perfect information about the stimulus. Simulations further show that our model reproduces the fish refuge tracking Bode plot across a wide frequency range. These results establish the theoretical validity of combining the IMP with an adaptive identification process and provide a basic framework in adaptive sensorimotor control.

  PublisherDOI

• Nullspace Adaptive Velocity Controller for Ground Vehicles: Theory and Experimental Evaluation

  IEEE Robotics and Automation Letters · 2025-05-22

  articleSenior author

  We report a novel stable Model-Based Adaptive Velocity Tracking Controller (AVTC) for ground vehicles capable of asymptotically exactly tracking longitudinal and yaw reference velocities and simultaneously adaptively identifying unknown plant parameters and actuator parameters. The reported AVTC is developed for velocity control of the commonly accepted three degree-of-freedom second-order dynamic “bicycle” model for ground vehicles. A Lyapunov analysis shows asymptotic stability of the velocity tracking error in longitudinal and yaw velocities, boundedness of all signals, and convergence of the adaptive parameter estimates. A performance evaluation of the proposed AVTC is reported including numerical simulation evaluation and experimental evaluation that corroborates the analytical predictions of stability and tracking, and compares its performance to its non-adaptive counterpart and two alternative controllers. AVTC only requires body-frame velocities and control input signals, and robustly detects, quantitatively identifies, and compensates dynamically in real-time for faults arising from changes to plant, actuator, and environmental parameters during operations.

  PublisherDOI

• Multidisciplinary characterisation of the biodiversity, geomorphology, oceanography and glacial history of Bowditch Seamount in the Sargasso Sea

  Deep Sea Research Part I Oceanographic Research Papers · 2024-06-12 · 2 citations

  articleOpen access

  The first multidisciplinary characterisation of Bowditch Seamount in the Sargasso Sea was conducted to provide new baseline knowledge of the biodiversity, geomorphology, oceanography and glacial history of this seamount. A dropframe camera transect 1,483–1,562 m deep on the seamount documented 77 megafaunal taxa including Vulnerable Marine Ecosystem indicator taxa such as sponges, cold-water corals, and stalked crinoids. Seabed terrain analysis of multibeam echosounder data showed species varied significantly along this transect in response to local geomorphological variability (R2adj = 31%, p<0.0001), with changes in seafloor relief and substrata driving species composition over the seamount. 14C-calibrated and 230Th-ages of fossil corals (Desmophyllum dianthus) collected by Van Veen grabs 1,517 m deep showed corals thrived on the seamount ∼24 ka BP and ∼17 ka BP. Abrupt excursions between higher and lower radiogenic εNd-composition values of the skeletons suggested that D. dianthus persisted on the seamount over times of southern source water input and detrital sediments from the melting Laurentide Ice Sheet, respectively. In agreement with other studies from the western North Atlantic, living D. dianthus were absent in the contemporary setting at these depths, and suggest a significant re-organisation of the seamount community since the deglacial when ice-rafted debris of carbonates likely resulted in a lower aragonite compensation depth allowing D. dianthus to proliferate at deeper depths. New conductivity-depth-temperature profiling revealed the seamount at these depths is now bathed by highly oxygenated Labrador Sea Water (LSW) formed at high latitudes. Co-analysis of a newly constructed 70-year long time series of temperature and salinity for the Labrador Sea and Bermuda regions revealed a 10-year transit time from high latitudes to Bowditch Seamount. This multidisciplinary approach shows how geomorphology drives local biodiversity patterns, but also how upstream climatic forcing in subpolar regions may influence Bermuda’s subtropical seamount ecosystem.

  PublisherDOI

• Adaptive Identification of Second-Order Mechanical Systems with Nullspace Parameter Structure: Stability and Parameter Convergence

  2024-12-16

  articleSenior author

  The relationships between persistence of excitation (PE) conditions and asymptotically stable convergence of parameter estimates are well-known for adaptive systems where stability and convergence are derived with respect to the origin of a combined state error and parameter estimation error system. We address a class of second-order mechanical systems in which the true parameters are, rather than one single point in parameter space, members of a nullspace defined by feasible evolutions of a regressor matrix. Differences within the set of true parameters are unobservable, requiring a new characterization of PE and parameter convergence. We report an adaptive identification (AID) approach for this class of systems and show local stability and parameter estimate convergence to the true parameter set under a subspace PE condition. This approach is applicable to many second-order mechanical systems, including robot arms and undersea, land, aerial, and space vehicles, and enables a more complete parameterization of uncertainty in the dynamics, e.g. enabling simultaneous AID of plant and actuator parameters for mechanical systems.

  PublisherDOI

• Nullspace Adaptive Identification of Plant and Actuator Model Parameters for Underactuated Ground Vehicles: Theory and Experimental Evaluation

  IFAC-PapersOnLine · 2024-01-01 · 2 citations

  articleOpen accessSenior authorCorresponding

  This paper reports a novel Nullspace Adaptive Identification (NSAID) algorithm to estimate plant and actuator model parameters for an underactuated ground vehicle with dynamics represented by a 3 degree-of-freedom second-order dynamic model, and reports an evaluation of its performance in simulation and experiments. Precise identification of ground vehicle plant and actuator model parameters is critical for physically realistic model-based simulation, control, navigation, and fault detection. However, ground vehicle plant model parameters, such as vehicle mass, moments of inertia, tire cornering stiffness and actuator model parameters such as motor torque constants are generally not possible to estimate a priori from first principles, and can change with varying payloads, configurations, and driving environments, and thus must be determined experimentally. Some parameter identification methods such as least squares regression depend on acceleration measurements, and most identification methods assume a priori knowledge of actuator parameters. In contrast, NSAID estimates plant and actuator parameters simultaneously, does not require acceleration measurements, can be utilized offline or online during vehicle operation, and can be applied with open or closed-loop control.

  PublisherDOI

• Nullspace Adaptive Model-Based Trajectory-Tracking Control for a 6-DOF Underwater Vehicle with Unknown Plant and Actuator Parameters: Theory and Preliminary Simulation Evaluation

  2024-05-13 · 3 citations

  articleSenior author

  We report a novel model-based nullspace adaptive trajectory-tracking control (NS-ATTC) algorithm for fully-actuated 6-degree-of-freedom (DOF) underwater vehicles which estimates unknown plant and actuator model parameters simultaneously. We provide a stability and convergence analysis with proof of asymptotically stable tracking error convergence, as well as a preliminary simulation study demonstrating 6-DOF trajectory tracking. The NS-ATTC algorithm does not require acceleration instrumentation and provides a stable online parameter estimate, enabling robust model-based autonomy.

  PublisherDOI

• A Hybrid Dynamical Model for Robotic Underwater Vehicles when Submerged or Surfaced: Approach and Preliminary Evaluation

  2024-05-13

  articleSenior author

  This paper reports a numerical method for modeling underwater vehicle (UV) interactions with the free surface using a finite-dimensional dynamical plant model. Although finite-dimensional plant models of fully submerged UV behavior are well-established, they are unable to model the ubiquitous condition of a UV operating at or near the free surface. We report a Monte Carlo-based hybrid model approach for calculating the buoyancy and righting moment of a partially or fully submerged UV in order to model interactions with the free surface. We also report a preliminary evaluation of the hybrid model in numerical simulations, comparing the hybrid model’s performance to that of a model for fully submerged UVs and to the experimentally observed behavior of an actual vehicle while fully submerged and while interacting with the free surface. The results of this preliminary study suggest that the proposed hybrid approach may offer a simple and practical method for modeling UV behavior when submerged or interacting with the free surface.

  PublisherDOI

• Stable nullspace adaptive parameter identification of 6 degree-of-freedom plant and actuator models for underactuated vehicles: Theory and experimental evaluation

  The International Journal of Robotics Research · 2023-10-01 · 10 citations

  articleSenior authorCorresponding

  Model-based approaches to navigation, control, and fault detection that utilize precise nonlinear models of vehicle plant dynamics will enable more accurate control and navigation, assured autonomy, and more complex missions for such vehicles. This paper reports novel theoretical and experimental results addressing the problem of parameter estimation of plant and actuator models for underactuated underwater vehicles operating in 6 degrees-of-freedom (DOF) whose dynamics are modeled by finite-dimensional Newton-Euler equations. This paper reports the first theoretical approach and experimental validation to identify simultaneously plant-model parameters (parameters such as mass, added mass, hydrodynamic drag, and buoyancy) and control-actuator parameters (control-surface models and thruster models) in 6-DOF. Most previously reported studies on parameter identification assume that the control-actuator parameters are known a priori. Moreover, this paper reports the first proof of convergence of the parameter estimates to the true set of parameters for this class of vehicles under a persistence of excitation condition. The reported adaptive identification (AID) algorithm does not require instrumentation of 6-DOF vehicle acceleration, which is required by conventional approaches to parameter estimation such as least squares. Additionally, the reported AID algorithm is applicable under any arbitrary open-loop or closed-loop control law. We report simulation and experimental results for identifying the plant-model and control-actuator parameters for an L3 OceanServer Iver3 autonomous underwater vehicle. We believe this general approach to AID could be extended to apply to other classes of machines and other classes of marine, land, aerial, and space vehicles.

  PublisherDOI

• The Roles of Autonomy and Assurance in the Future of Uncrewed Aircraft Systems in Low-Altitude Airspace Operations

  Computer · 2023-07-01 · 2 citations

  article

  We are extending the research in the area of uncrewed aircraft systems by further investigating safety in more realistic and congested airspace operations. These investigations allow us to more realistically examine the roles that autonomy and assurance should play in future airspace operations.

  PublisherDOI

Recent grants

• NIH Grant R01EB002963

  NIH · $2.0M · 2010

• Collaborative Research: ITR-(ASE)+(DMC_INT): New Methods for the Exploration of Deep-Sea Hydrothermal Vents with Multiple Autonomous Underwater Robotic Vehicles

  NSF · $607k · 2004–2008

• RI: Small: Robust Model-Based Identification, Navigation, and Control of Underactuated Underwater Vehicles

  NSF · $500k · 2019–2024

• RI: Small: Fast, Cheap, and In Control: New Methods for Precision Navigation of Low-Cost Autonomous Underwater Vehicles for Ocean Science

  NSF · $450k · 2013–2017

• Development of a Low-Cost True-North Seeking Fiber Optic Gyrocompass and Integrated Doppler Navigation System for Precision Navigation of Underwater Vehicles for Ocean Science

  NSF · $580k · 2014–2018

Frequent coauthors

• Gábor Fichtinger

  Queen's University

  70 shared

• D. Yoerger

  Woods Hole Oceanographic Institution

  62 shared

• Axel Krieger

  Johns Hopkins University

  61 shared

• Ergin Atalar

  Bilkent University

  58 shared

• Robert C. Susil

  Johns Hopkins Hospital

  53 shared

• Kevin Camphausen

  National Cancer Institute

  48 shared

• Jonathan Coleman

  45 shared

• C. Norman Coleman

  National Cancer Institute

  43 shared

Labs

• Dynamical Systems and Control Laboratory (DSCL)PI

Awards & honors

• NSF CAREER Award
• Office of Naval Research Young Investigator Award
• Fellow of the Institute of Electrical and Electronics Engine…
• William H. Huggins Excellence in Teaching Award
• Alumni Excellence in Teaching Award