About

Manoranjan Majji is an Assistant Professor and the Director of the LASR Laboratory at the Department of Aerospace Engineering, Texas A&M University. His research interests encompass structural systems, computational vision and sensor systems, astronautics and dynamical systems, as well as aerospace robotics and autonomous systems. His work focuses on advancing the understanding and development of autonomous and robotic systems within aerospace engineering, contributing to the fields of sensor integration, system dynamics, and autonomous navigation.

Research topics

• Computer Science
• Physics
• Geography
• Artificial Intelligence
• Environmental science
• Engineering
• Environmental resource management
• Acoustics
• Business
• Ecology
• Environmental health
• Astrobiology
• Medicine
• Architectural engineering
• Operating system
• Environmental planning
• Astronomy
• Mechanics
• Aerospace engineering
• Computer vision
• Mathematics
• Classical mechanics

Selected publications

• Direct Pseudospectral Optimal Control by Orthogonal Polynomial Integral Collocation

  Journal of Guidance Control and Dynamics · 2026-04-13

  preprintOpen accessSenior author

  This paper details a methodology to transcribe an optimal control problem into a nonlinear program for generation of the trajectories that optimize a given functional by approximating only the highest-order derivatives of a given system’s dynamics. The underlying method uses orthogonal polynomial integral collocation by which successive integrals are taken to approximate all lower-order states. Hence, one set of polynomial coefficients can represent an entire coordinate’s degree of freedom. Specifically, Chebyshev polynomials of the first and second kinds and Legendre polynomials are used over their associated common interpolating grids derived from the bases’ roots and extrema. Simple example problems compare different polynomial bases’ performance to analytical solutions. The planar circular orbit raising problem is used to verify the method with solutions obtained by other pseudospectral methods in literature. Finally, a rocket landing flip maneuver problem is solved to demonstrate the ability to solve complex problems with multiple states and control variables with constraints. Simulations establish this method’s performance and reveal that the polynomial/node choice for a given problem notably affects the performance.

  PublisherOA PDFDOI

• Projective Transformations for Regularized Central-Force Dynamics: Hamiltonian Formulation

  ArXiv.org · 2025-06-27

  preprintOpen access

  This work introduces a Hamiltonian approach to regularization and linearization of central-force particle dynamics through a new canonical extension of the so-called "projective decomposition". The regularization scheme is formulated within the framework of classic analytical Hamiltonian dynamics as a redundant-dimensional canonical/symplectic coordinate transformation, combined with an evolution parameter transformation, on extended phase space. By considering a generalized version of the standard projective decomposition, we obtain a family of such canonical transformations which differ at the momentum level. From this family of transformations, a preferred coordinate set is chosen that possesses a simple and intuitive connection to the particle's local reference frame. Using this transformation, closed-form solutions are readily obtained for inverse-square and inverse-cubic radial forces, or any superposition thereof. Governing equations are numerically validated for the classic two-body problem incorporating the J2 gravitational perturbation.

  PublisherOA PDFDOI

• On-Manifold Low-Thrust Rephasing of Quasi-Periodic Orbits

  arXiv (Cornell University) · 2025-07-10

  preprintOpen access

  A bi-level optimal control framework is introduced to solve the low-thrust re-phasing problem on quasi-periodic invariant tori in multi-body environments where deviations away from the torus during maneuver are considered unsafe or irresponsible. It is shown for a large class of mechanical systems that conformity to the torus manifold during periods of non-zero control input is infeasible. The most feasible trajectories on the torus surface are generated through the minimization of fictitious control input in the torus space using phase space control variables mapped via the torus function. These reference trajectories are then transitioned to the phase space both through a minimum tracking error homotopy and minimum time patched solutions. Results are compared to torus agnostic low-thrust transfers using measures of fuel consumption, cumulative torus error, and coast time spent on the torus during maneuver. Modifications to the framework are made for the inclusion of quasi-periodically forced dynamical systems. Lastly, minimum time recovery trajectories with free final torus conditions expose the disparity between the proposed framework and torus agnostic approaches. Examples are drawn from the circular and elliptical restricted three-body problems.

  PublisherOA PDFDOI

• The Linear Parametrization of Two Dimensional Tori Families in the Restricted Three Body Problem

  Research Square · 2025-04-25

  preprintOpen access
  PublisherOA PDFDOI

• Validation of In-Space Servicing, Assembly, and Manufacturing Missions Using Simscape Multibody

  2025-06-30

  articleSenior author

  This paper presents the simulation and validation of a generalized spacecraft and robotic platform for In-Space Servicing, Assembly, and Manufacturing (ISAM) missions. A multibody dynamics model used for simulating ISAM missions is created with a combination of Matlab scripts and Simulink modeling with the intent of modular testing of different satellite buses and manipulators. The resulting model is validated using an experimental setup using a Stewart platform and a Universal Robots manipulator, demonstrating the similar results in the base reaction forces and torques with a matched trajectory.

  PublisherDOI

• Development and Validation of Velocimeter LIDAR Simulator

  2025-01-03

  articleSenior author

  Velocimeter LiDAR sensors provide high-fidelity altimetry and velocimetry essential for precision navigation and safe landing operations. This work presents the development and experimental validation of a velocimeter LiDAR simulation framework. Using ray tracing techniques, we develop a functional model that generates synthetic point clouds and Doppler velocity measurements from virtual scene descriptions. Our methodology incorporates ground truth kinematic states to reconstruct experimental sensor trajectories, enabling direct comparison between synthetic and real-world measurements. Through statistical analysis of point cloud distributions and Doppler velocity measurements, we quantitatively evaluate the simulation fidelity and validate the sensor model performance. Our results demonstrate strong agreement between synthetic and real measurements using median absolute deviation metrics and point cloud variance analysis. The validated simulation framework provides a reliable platform for generating synthetic datasets that emulate real-world LiDAR scanner behavior, advancing our understanding of velocimeter LiDAR sensor performance in simulated environments.

  PublisherDOI

• A Rapid Trajectory Optimization and Control Framework for Resource-Constrained Applications

  2025-07-08

  articleSenior author

  This paper presents a computationally efficient model predictive control formulation that uses an integral Chebyshev collocation method to enable rapid operations of autonomous agents. By posing the finite-horizon optimal control problem and recursive re-evaluation of the optimal trajectories, minimization of the L2 norms of the state and control errors are transcribed into a quadratic program. Control and state variable constraints are parameterized using Chebyshev polynomials and are accommodated in the optimal trajectory generation programs to incorporate the actuator limits and keep- out constraints. Differentiable collision detection of polytopes is leveraged for optimal collision avoidance. Results obtained from the collocation methods are benchmarked against the existing approaches on an edge computer to outline the performance improvements. Finally, collaborative control scenarios involving multi-agent space systems are considered to demonstrate the technical merits of the proposed work.

  PublisherDOI

• Tensegrity system dynamics in fluids

  Nonlinear Dynamics · 2025-03-22 · 2 citations

  articleOpen access
  PublisherOA PDFDOI

• Linear and Regular Kepler-Manev Dynamics via Projective Transformations: A Geometric Perspective

  ArXiv.org · 2025-07-09

  preprintOpen access

  This work presents a geometric formulation for transforming nonconservative mechanical Hamiltonian systems and introduces a new method for regularizing and linearizing central force dynamics -- in particular, Kepler and Manev dynamics -- through a projective transformation. The transformation is formulated as a configuration space diffeomorphism (rather than a submersion) that is lifted to a cotangent bundle (phase space) symplectomorphism and used to pullback the original mechanical Hamiltonian system, Riemannian kinetic energy metric, and other key geometric objects. Full linearization of both Kepler and Manev dynamics (in any finite dimension) is achieved by a subsequent conformal scaling of the projectively-transformed Hamiltonian vector field. Two such conformal scalings are given, both achieving linearization. Arbitrary conservative and nonconservative perturbations are included, with closed-form solutions readily obtained in the unperturbed Kepler or Manev cases.

  PublisherOA PDFDOI

• Safe Multi-agent Satellite Servicing with Control Barrier Functions

  ArXiv.org · 2025-02-13

  preprintOpen accessSenior author

  The use of control barrier functions under uncertain pose information of multiple small servicing agents is analyzed for a satellite servicing application. The application consists of modular servicing agents deployed towards a tumbling space object from a mothership. Relative position and orientation of each agent is obtained via fusion of relative range and inertial measurement sensors. The control barrier functions are utilized to avoid collisions with other agents for the application of simultaneously relocating servicing agents on a tumbling body. A differential collision detection and avoidance framework using the polytopic hull of the tumbling space object is utilized to safely guide the agents away from the tumbling object.

  PublisherOA PDFDOI

Frequent coauthors

• John L. Junkins

  78 shared

• Puneet Singla

  Pennsylvania State University

  43 shared

• Robert E. Skelton

  Texas A&M University

  42 shared

• Raman Goyal

  42 shared

• James D. Turner

  Texas A&M University

  25 shared

• Muhao Chen

  Texas A&M University

  21 shared

• Caleb Peck

  21 shared

• Davis W. Adams

  18 shared

Labs

• LASR LaboratoryPI

Education

• PhD, Aerospace Engineering

  Texas A&M University

  2009