Library · Simulation & modelling
What Kinematic & Dynamics Simulation got wrong, from 61 theses
Summary written by a model from the records below: The records describe diverse challenges in kinematic and dynamic simulation across robotics, biomechanics, vehicle systems, and aerospace engineering. Researchers frequently encounter model discrepancies, unmodeled physical interactions, kinematic singularities, and solver convergence failures when balancing dynamic fidelity against computational tractability. These records come from graduate theses, 2021 to 2026, each labeled with its degree where the repository states it, and each links to its thesis. They were extracted by language models reading the full text, so treat each as a lead to read, not a verdict.
Plus 10 problems the authors left open, listed at the end.
Failure modes, by theses reporting them
Select a mode to jump to its records.
Kinematic and inertial models fail when omitting aerodynamic, structural flexibility, or actuation dynamics
Simplified rigid-body and kinematic models produce inaccurate trajectories and unstable predictions when neglecting forces such as aerodynamic downwash, thrust, structural flexibility, and dynamic muscle properties. Incorporating complete dynamic model knowledge and higher-fidelity structural formulations consistently outperforms purely inertial or kinematic approximations.
Tried and failed
musculoskeletal simulation omitting muscle force-length-velocity dynamics applied to biomechanical gait simulation. Outcome: unstable. Reason: neglecting dynamic muscle properties caused reserve actuator forces to exceed acceptable validity thresholds
Predicting lower limb kinematics and kinetics from internal measurement units using deep learning · Imperial · PhD
Tried and failed
centroidal dynamics with full kinematics trajectory optimization applied to humanoid dynamic jumping maneuvers. Reason: omits joint torque and electrical power limits, yielding physically infeasible trajectories
A Model-Based Planning and Control Framework for Parkour-Style Legged Locomotion · MIT · PhD
Lost to a baseline
In autonomous racing, BestCase MPC with full dynamic model knowledge beat BayesRace GP-corrected kinematic model prior to multi-lap model updates
Methods For Data-Driven Model Predictive Control · Penn · PhD
Tried and failed
free-floating rigid body dynamics modeling applied to spacecraft attitude during in-situ manufacturing. Outcome: did not generalise. Reason: neglected metal springback effects caused unmodeled rotational steps and vibrations
Rapid In-Space Assembly and Manufacturing of Large Reticulated Truss Structures · MIT · PhD
Tried and failed
inertial-only multibody dynamics modeling applied to aerodynamic pitch angle prediction. Outcome: worse than baseline. Reason: aerodynamic moments acted in opposition to inertial forces, which were neglected
Multibody Dynamics of Aeromechanical Systems · Virginia Tech · Doctorate
Tried and failed
articulating nose for direct roll control applied to guided projectile attitude stabilization. Reason: out-of-plane deflections generate weak roll moments that are strongly coupled to longitudinal dynamics
Smart Projectile Performance Augmentation Using an Articulating Nose · Georgia Tech · PhD
Tried and failed
static wind tunnel testing for drag estimation applied to multirotor aerodynamic calibration. Outcome: did not generalise. Reason: fixed rotors neglect dynamic rotor aerodynamics and induced airflow present during flight
Spatially distributed Wind and Turbulence Measurements with a Fleet of Unmanned Aerial Systems · Tübingen · PhD
Tried and failed
Orthogonal function modeling with Kalman filter estimation applied to unsteady vehicle aerodynamic dynamics. Outcome: did not generalise. Reason: Omission of dynamic thrust modeling and accumulated state estimation errors under severe environmental disturbances.
Identification of Unsteady Flight Dynamic Models and Model-based Wind Estimation with Flight Test Validation · Virginia Tech · Doctorate
Tried and failed
neural ODE residual learning without domain physics applied to aerodynamic torque and proximity dynamics. Outcome: did not generalise. Reason: omitting nominal downwash aerodynamic models prevented accurate out-of-distribution torque predictions in close-proximity conditions
Learning-based Model Predictive Control for Aerial Vehicles · Penn · PhD
Tried and failed
single-component proxy modeling with partial loading applied to multi-blade rotor aeroelastic kinematics. Outcome: did not generalise. Reason: isolated blade aerodynamic trimming failed to reproduce multi-blade aerodynamic interactions and structural deformations
Computational Investigation of Separated Flow and Stall Events on Rotating Systems · Georgia Tech · PhD
Lost to a baseline
Beam model overpredicted baseline wing torsional deformation compared to shell FEM due to the kinematic omission of rib stiffness in the beam formulation
A Flexible Methodology for Analysis and Optimization of Unconventional Wing Structural Geometries Using a Computationally Efficient Aeroelastic Model · Georgia Tech · PhD
Considered and rejected
Considered and rejected: Rejected purely kinematic TP approaches because neglecting external forces (thrust, drag, wind) severely degrades prediction accuracy across dynamic flight phases
Trajectory modelling and execution for multi-Unmanned Aerial Vehicle applications · Imperial · PhD
Linear and steady-state assumptions fail to capture nonlinear transient dynamics
Linearized state-space representations and steady-state dynamic analyses fail when applied to systems with complex transient behaviors, vehicle steering geometry, or control saturations. These simplified models systematically diverge under rapid maneuvers or operating point shifts, requiring nonlinear formulations to maintain fidelity.
Tried and failed
linearization to state-space models applied to nonlinear multibody transient dynamics. Outcome: did not generalise. Reason: produced inaccurate transient responses and was computationally inefficient across varying operating points
A Multi-fidelity Modeling Approach for Vehicle Performance Tuning · Georgia Tech · PhD
Tried and failed
extended Kalman filtering with kinematic motion models applied to trajectory prediction of maneuvering targets. Outcome: worse than baseline. Reason: linear kinematic assumptions cannot accurately capture complex nonlinear maneuvering dynamics
Data-driven Target Tracking and Hybrid Path Planning Methods for Autonomous Operation of UAV · Virginia Tech · Doctorate
Tried and failed
Multiple linear regression baseline applied to Traffic incident delay estimation. Outcome: worse than baseline. Reason: Linear assumptions cannot capture complex nonlinear spatial-temporal traffic dynamics
Tried and failed
linearised reduced-order structural dynamics modelling applied to flexible wing aeroservoelastic control. Reason: linear models failed to accurately capture in-plane structural dynamics compared to out-of-plane modes
Nonlinear aeroservoelastic modelling for design and performance evaluation of gust load alleviation systems for flexible air vehicles · Imperial · PhD
Tried and failed
linear system identification of inverse dynamics applied to vehicle braking systems. Outcome: did not generalise. Reason: linear models failed to capture non-linearities like ABS activation and traction saturation
Adaptive Longitudinal and Lateral Control for Autonomous Vehicles: High-Speed Platooning of Articulated Trucks · Virginia Tech · Doctorate
Tried and failed
constant steering ratio in kinematic model applied to vehicle trajectory prediction. Outcome: did not generalise. Reason: nonlinear steering geometry causes large trajectory divergence under moderate and rapid steering inputs
Parameter Identification and Validation of a Control-Oriented Vehicle Dynamics Model for an Autonomous Chevrolet Bolt EUV · Virginia Tech · Master's
Considered and rejected
Considered and rejected: Discarded second- and third-order polynomial regression models with a single independent variable in vehicle dynamics objectivization because they yielded no improved performance over linear models.
Considered and rejected
Considered and rejected: Rejected standard 1D discrete kinematic model (in-finite bandwidth inner loop) because real vehicle transient response did not match simulation; replaced with first-order inner loop dynamics (tau = 0.26 s)
Constant Time Delay Leader Following for Mobile Robots by using Model Predictive Control Tuned on Estimation Uncertainties · Queen's University · Master's
Considered and rejected
Considered and rejected: Rejected model-based RL and conventional convex optimization control policies due to large biases from oversimplification of complex nonlinear microscopic traffic dynamics.
Modelling urban street configurations for Autonomous Vehicle flows · Imperial · PhD
Non-smooth dynamics and local minima cause kinematic optimization and inverse solvers to fail
Numerical inverse kinematics, trajectory optimization, and differentiable physics simulations frequently diverge or stall when encountering non-smooth physical bounds, kinematic irregularities, and severe gradient variance. Analytical inversions and gradient-based searches become mathematically intractable due to the numerous local minima introduced by forward kinematics equations and muscle contraction models.
Lost to a baseline
Differential inverse kinematics achieved lower RMSE (0.0036m x, 0.0044m y, 0.00055m z) than gradient projection (0.0037m, 0.0034m, 0.0070m) and ANFIS (0.1309m, 0.0209m, 0.1261m), but failed joint limit constraints.
Development of Methodologies, Mechatronic Solutions and Controls for Upper Body Rehabilitative Robotics · Politecnico di Torino · PhD
Lost to a baseline
Forward kinematics with 6 base DoFs yielded higher positional error than inverse kinematics optimization using the same 6 DoFs
An integrative computational modeling approach for Drosophila motor control · EPFL · PhD
Considered and rejected
Considered and rejected: Rejected direct inverse kinematics (IK) neural network learning because it is anticausal, cannot exploit redundancy, and requires real-time distal pose measurements unavailable in surgery
Robot model learning and optimal control towards safer robotic surgery · Imperial · PhD
Tried and failed
quadratic programming with strict physiological bound constraints applied to musculoskeletal inverse dynamics torque estimation. Outcome: did not converge. Reason: kinematic irregularities and non-smooth dynamics made strictly bounded constraints mathematically infeasible
Understanding motor control and impairment: An upper-limb model for muscular assessment · EPFL · PhD
Tried and failed
trajectory optimization with compliant flexible elements applied to legged robot locomotion. Outcome: did not converge. Reason: modeling physical leaf springs in full rigid-body dynamics made solver convergence extremely difficult
Controlling Contact Transitions for Dynamic Robots · Penn · PhD
Tried and failed
model-free reinforcement learning with reduced-order state applied to bipedal locomotion control. Outcome: did not converge. Reason: simplified low-dimensional state representation lacked sufficient dynamics information for whole-body motion synthesis
Towards versatile, high-performing and interactive humanoids · UT Austin · PhD
Tried and failed
program synthesis with forward kinematics constraints applied to manipulator inverse kinematics optimization. Outcome: did not converge. Reason: forward kinematics equations introduced numerous local minima, making numerical optimization intractable
Task-Based Design Synthesis Of Modular Manipulators · Cornell · PhD
Tried and failed
Restricting rhythmic pattern generation to proximal actuators applied to Neuromechanical forward dynamics gait generation. Outcome: did not converge. Reason: Failed to generate rhythmic locomotion when distal joint muscle pattern inputs were zeroed
Considered and rejected
Considered and rejected: Rejected computing control inputs via continuous analytical inverse dynamics because redundant, non-linear activation dynamics and ODE-based muscle contraction models prohibit direct mathematical inversion.
Neuro-musculoskeletal Models: A Tool to Study the Contribution of Muscle Dynamics to Biological Motor Control · Tübingen · PhD
Considered and rejected
Considered and rejected: Searching directly over joint angles theta using forward kinematics equations (rejected due to highly non-linear functions creating numerous local minima; replaced by parameterizing states P directly)
Task-Based Design Synthesis Of Modular Manipulators · Cornell · PhD
Tried and failed
gradient estimation through differentiable physics simulation applied to stiff or discontinuous dynamical systems. Outcome: unstable. Reason: gradients suffer from empirical bias, zero variance illusion, and severe variance blowup in discontinuous dynamics
Leveraging Structure for Efficient and Dexterous Contact-Rich Manipulation · MIT · PhD
Kinematic models neglect physical contact mechanics, friction, and mechanical compliance
Simulating robotic manipulation, locomotion, and material forming using purely kinematic or frictionless assumptions leads to severe prediction errors and unnatural sliding behaviors. Omitting joint compliance, mechanical interlocking, and soft-tissue or interface friction artificially constrains physical dynamics and causes tracking failures.
Tried and failed
multi-axis force-controlled robotic kinematic simulation applied to isolated knee replacement implant kinematics. Reason: lack of soft-tissue constraints caused paradoxical anterior femoral sliding under posterior drawer loads
Robotic testing of total knee replacement designs · Imperial · PhD
Tried and failed
contact-rich rigid body dynamics simulation applied to mechanical adhesion in swarm robotics. Reason: Microscopic mechanical interlocking could not be simulated natively, requiring artificial constraint joints to match physical adhesion.
Collision Induced Self Organization in Shape Changing Robots · Georgia Tech · PhD
Considered and rejected
Considered and rejected: Kinematic draping simulations (KDS) were rejected for multi-ply forming analysis due to their fundamental inability to model friction, compaction, or out-of-plane bending physics.
Automated forming of multi-ply non-crimp fabric structures · Nottingham · PhD
Tried and failed
kinematics-based series elastic actuator force modeling applied to robotic exoskeleton force estimation. Reason: unmodeled friction and compliance/deformations in mechanical linkages caused high force prediction errors
Vision-Based Force Planning and Voice-Based Human-Machine Interface of an Assistive Robotic Exoskeleton Glove for Brachial Plexus Injuries · Virginia Tech · Doctorate
Tried and failed
training regression models on frictionless simulation data applied to mechanical stiffness estimation. Outcome: did not generalise. Reason: frictionless simulation failed to capture real-world friction dynamics leading to catastrophic evaluation errors
ULTRASONIC IMAGING AND TACTILE SENSING FOR ROBOTIC SYSTEMS · Georgia Tech · PhD
Tried and failed
prescribed displacement boundary condition in FE modeling applied to unconstrained frictional sliding dynamics. Outcome: did not generalise. Reason: prescribed kinematics artificially constrained physical contact dynamics and sliding interface behavior
Variable frictional interface behaviour for nonlinear dynamic response control · Imperial · PhD
Tried and failed
continuum kinematic modeling with idealized contact mechanics applied to locomotion speed prediction of articulated robots. Outcome: did not generalise. Reason: rigid link interiors caused unintended sliding drag instead of idealized pure rolling ground contact
Shape-centric Modeling for Control of Snake-like Robots · Georgia Tech · PhD
Considered and rejected
Considered and rejected: Rejected piece-wise function kinematic modeling of the 3-finger gripper due to slow step simulation and inability to handle contact events.
Towards Optimal Grasping Of Unknown Objects Using Deep Reinforcement Learning · York University · Master's
Considered and rejected
Considered and rejected: Rejected analytical kinematic fishnet/mapping models because they neglect forming loads, frictional interactions, and bending stiffness necessary for defect prediction.
Thermomechanical forming simulation for fibre reinforced thermoplastic laminates · Nottingham · PhD
Considered and rejected
Considered and rejected: Rejected simulating wheel-ground contact dynamics for the Fetch robot base, choosing kinematic navigation mesh movement instead.
From Multimodal LLMs to Generalist Embodied Agents · Georgia Tech · PhD
Policies and open-loop trajectories fail during sim-to-real transfer due to unmodeled dynamics
Control policies and trajectory plans optimized entirely in simulation fail when executed on physical robotic hardware without real-time adaptation. Unmodeled contact dynamics, actuator discrepancies, and state observation errors create a substantial sim-to-real gap that causes alignment and tracking breakdowns.
Tried and failed
open-loop transfer of simulation-optimized trajectories to hardware applied to locomotion controller for physical robots. Outcome: did not generalise. Reason: sim-to-real gap and unmodeled contact dynamics caused unpredictable execution without feedback
Robot Graph Grammars: Towards Custom Robots for Every Task · MIT · PhD
Tried and failed
direct sim-to-real transfer of reinforcement learning policies applied to embodied robotic navigation. Outcome: did not generalise. Reason: unmodeled real-world physical dynamics mismatch between the simulation environment and physical hardware
4D audio-visual learning: a visual perspective of sound propagation and production · UT Austin · PhD
Tried and failed
direct sim-to-real transfer of synthesized control policies applied to real-world robotic control. Outcome: did not generalise. Reason: simulated dynamics did not match real-world physical interactions without real-time adaptation
Leveraging program synthesis for robust long-term robot autonomy via interactive learning and adaptation · UT Austin · PhD
Tried and failed
Off-the-shelf CAD plugin for robotic path simulation applied to Industrial robotic toolpath verification. Reason: Kinematic model discrepancies between simulation software and hardware controller
Design-to-Fabrication Workflow for Raw-Sawn-Timber using Joinery Solver · EPFL · PhD
Tried and failed
open-loop trajectory tracking applied to contact-rich robotic assembly insertions. Outcome: did not generalise. Reason: unmodeled contact dynamics and real-world execution errors caused alignment failures without feedback
Scalable Assembly of General Objects · MIT · PhD
Considered and rejected
Considered and rejected: Rejected end-to-end DRL learning of guidance and low-level control directly from states to actuator forces/torques because policy overfits simulated dynamics and fails during sim-to-reality transfer.
Deep Reinforcement Learning as Guidance for Aerospace Robotics · Carleton University · PhD
Considered and rejected
Considered and rejected: Rejected direct velocity-based state observations in favor of position-based observations due to difficulties in accurately modeling robot dynamics during sim-to-real transfer.
Scalable Assembly of General Objects · MIT · PhD
Tried and failed
Direct open-loop execution of extracted trajectory priors applied to robotic grasping and manipulation tasks. Outcome: did not generalise. Reason: Demonstration trajectories without interactive exploration cannot handle real-world physical and kinematic discrepancies.
Teaching Robots using Interactive Imitation Learning · Virginia Tech · Doctorate
Tried and failed
model predictive control with learned neural kinematics applied to trajectory tracking in flexible robot manipulation. Outcome: unstable. Reason: model inaccuracies and unhandled uncertainty caused critical bound violations and tracking failure
Robot model learning and optimal control towards safer robotic surgery · Imperial · PhD
High-fidelity dynamic simulations incur excessive computational complexity and forward simulation overhead
Full multibody dynamic modeling and whole-body forward kinematics across all link points introduce prohibitive computational costs that limit interactive use and large-scale reinforcement learning. Researchers frequently reject dynamic models or complex relaxation schemes in favor of simplified kinematic approximations to achieve feasible cycle times.
Tried and failed
discrete event simulation for robot kinematics estimation applied to robotic process time estimation. Reason: discrete-event modeling lacked the physics fidelity required to accurately compute robotic movement and cycle times
Model-based Design Framework of Modular Hyperconnected Facilities: Experiments in the Building Prefabrication, Election, and Logistics Ecosystems · Georgia Tech · PhD
Tried and failed
ADMM convex relaxation combining distance and velocity applied to joint kinematic parameter estimation. Outcome: too slow. Reason: excessive computational complexity and high processing overhead
Precise Geolocation for Drones, Metaverse Users, and Beyond: Exploring Ranging Techniques Spanning 40 KHz to 400 GHz · Virginia Tech · Doctorate
Tried and failed
projective dynamics differentiable simulation applied to low degree of freedom soft-body dynamics. Outcome: worse than baseline. Reason: prefactorization overhead provides no advantage over exact Newton steps at small system dimensions
Differentiable Simulation Methods for Robotic Agent Design · MIT · PhD
Considered and rejected
Considered and rejected: Rejected solving Hamilton-Jacobi-Bellman PDEs for reachability due to intractable high dimensionality of multi-body humanoid dynamics.
Whole-body trajectory generation and control strategies for multi-contact robots · UT Austin · PhD
Considered and rejected
Considered and rejected: Rejected using OpenSim directly for large-scale RL due to extreme computational slowness and forward-dynamics instability.
Reinforcement Learning for Muscle-Driven Systems · Tübingen · PhD
Considered and rejected
Considered and rejected: Rejected using whole-manipulator observation models due to computational complexity of modeling forward kinematics across all link points
Learning to Make Decisions in Robotic Manipulation · MIT · PhD
Lost to a baseline
Kinematics-only LSTM had lower inference latency (213.14 ms) than the combined kinematics + vision model (562.86 ms)
Learning Based Sensorless Contact Detection for Haptic Feedback on the da Vinci Research Kit · Johns Hopkins · Master's
Rotational dynamics parameterizations suffer from kinematic singularities and coordinate frame ambiguities
Using standard Euler-angle parameterizations for aggressive spatial maneuvers leads to mathematical singularities and poor orientation distance metrics. Formulations in body reference frames or coordinate systems susceptible to algorithmic singularities are frequently replaced with inertial or Lie group representations.
Considered and rejected
Considered and rejected: Body reference frame control formulation: rejected in favor of inertial reference frame dynamics to formulate dynamic equations suitable for GP-MRAC and vector RKHS-MRAC
Data-Driven, Non-Parametric Model Reference Adaptive Control Methods for Autonomous Underwater Vehicles · Virginia Tech · Master's
Considered and rejected
Considered and rejected: Rejected Euler angles (Tait-Bryan) for spacecraft rotational dynamics representation due to representation ambiguity and kinematic singularities at pitch theta = pi/2.
Vision based Real-Time Navigation with Unknown and Uncooperative Space Target · Carleton University
Considered and rejected
Considered and rejected: Rejected using discrete-time inertial velocity from GNSS directly in the measured state vector y, favoring position kinematics for observer stability.
Nonlinear Observers for Aircraft Maneuvering in Wind · Virginia Tech · Doctorate
Considered and rejected
Considered and rejected: Rejected using raw IMU pitch in the pitch feedback loop, choosing whole-body orientation (WBO) pitch to reject tail acceleration dynamics.
No Watts Wasted: Spines and Tails for Agile Legged Locomotion · Penn · PhD
Considered and rejected
Considered and rejected: Rejected standard Euler-angle rotational dynamics parameterization in SRB MPC in favor of Variational Based Linearization on SO(3) to avoid kinematic singularities during dynamic motions
Real-Time Planning and Nonlinear Control for Robust Quadrupedal Locomotion with Tails · Virginia Tech · Master's
Considered and rejected
Considered and rejected: Rejected base-frame-based RCM kinematic formulations due to algorithmic singularities occurring independent of mechanical configuration
Development and Evaluation of Control Methods with Dynamic RCM Constraint on Surgical Robotics System in Minimally Invasive Surgery · Johns Hopkins · Master's
Left open by the authors
Problems the authors named and did not get to.
Left open
Estimate individual tendon tensions and build online-varying backlash and hysteresis models for tendon-driven surgical robots. Blocker: Requires the physical Micro-IGES surgical robot hardware or dedicated experimental apparatus to measure and validate tendon tension dynamics.
Robot model learning and optimal control towards safer robotic surgery · Imperial · PhD
Left open
Develop an optimal weight tuning method for the MPC cost function in surgical tendon-driven robot control. Blocker: Requires the physical Micro-IGES surgical robot setup or its proprietary kinematic simulation data
Robot model learning and optimal control towards safer robotic surgery · Imperial · PhD
Left open
Extend cross-learning to navigation problems featuring complex dynamics from human-machine interaction. Blocker: Vague task direction lacking specific formulation, targets, or interactive dynamics models
Graph Machine Learning Under Requirements · Penn · PhD
Left open
Compute lower-limb joint quasi-stiffness from perturbation walking kinematics and kinetics data and compare it to steady-state gait. Blocker: Requires experimental biomechanical gait perturbation data (motion capture and force plates) or specialized perturbation simulations.
An assessment of lower-limb joint quasi-stiffness during healthy and transtibial amputee walking · UT Austin · PhD
Left open
Train a machine learning model on human kinematic data to generate nominal crawling trajectories parameterized by worker body dimensions. Blocker: Requires a comprehensive motion-capture dataset of diverse human subjects crawling.
Analysis, Design, and Control of Supernumerary Robotic Limbs Coupled to a Human · MIT · PhD
Left open
Extend Complex Wrinkle Field kinematics to simulate dynamic cloth PDEs beyond boundary value interpolation. Blocker: Lacks specific mathematical formulations or numerical algorithms to couple full dynamic cloth equations with CWF kinematics
Complex wrinkle simulation and robust surface remeshing · UT Austin · PhD
Left open
Extend the optimal local truncation error method to simulate stationary and propagating cracks and non-linear partial differential equations. Blocker: High mathematical complexity with no specified formulation for non-linearities or crack propagation dynamics
Left open
Train machine learning models (Random Forest, SVM, Deep Learning) on LiDAR trajectory data to classify driver behavior instead of rule-based kinematic thresholds. Blocker: Access to the thesis author's roadside LiDAR trajectory dataset and proprietary VISSIM simulation environment.
Calibration of Microscopic Traffic Simulation Models for Proactive Safety Performance based on LiDAR Trajectory Data · Texas Tech · PhD
Left open
Perform scale-resolving simulations to model unsteady aerodynamics for active aerodynamic control of high-performance vehicles at extremely low ride heights. Blocker: Lack of specific proprietary vehicle geometry and boundary conditions from the original thesis
Analysis of active aerodynamics for high-performance vehicles · Cranfield · PhD
Left open
Develop and test model-based predictive control and autonomy algorithms within the multibody dynamics simulation framework. Blocker: Access to the thesis author's specific Simscape Multibody model files and vehicle parameters
Multibody dynamics modeling, validation, and analysis of a mobile off-road vehicle · Iowa State · PhD
Who has worked on this
Authors of the public theses cited on this page, most-cited first.
- Francesco Cursi · Imperial · PhD · 2022
Robot model learning and optimal control towards safer robotic surgery - Yunsheng Tian · MIT · PhD · 2025
Scalable Assembly of General Objects - Thais Campos de Almeida · Cornell · PhD · 2021
Task-Based Design Synthesis Of Modular Manipulators - Mariam Emara · Georgia Tech · PhD · 2026
A Multi-fidelity Modeling Approach for Vehicle Performance Tuning - Mohamed Ahmed Yehia Zakaria · Virginia Tech · Doctorate · 2026
Multibody Dynamics of Aeromechanical Systems - Hyunbin Kang · Virginia Tech · Master's · 2026
Parameter Identification and Validation of a Control-Oriented Vehicle Dynamics Model for an Autonomous Chevrolet Bolt EUV - Harsh G. Bhundiya · MIT · PhD · 2025
Rapid In-Space Assembly and Manufacturing of Large Reticulated Truss Structures - Andrew Szot · Georgia Tech · PhD · 2025
From Multimodal LLMs to Generalist Embodied Agents - Akash Vardhan · Georgia Tech · PhD · 2025
Collision Induced Self Organization in Shape Changing Robots - Matthew T. Chignoli · MIT · PhD · 2025
A Model-Based Planning and Control Framework for Parkour-Style Legged Locomotion - Cason Nicholas Butler · Georgia Tech · PhD · 2025
Smart Projectile Performance Augmentation Using an Articulating Nose - Sander Roger Holthof · Imperial · PhD · 2025
Robotic testing of total knee replacement designs
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