Mangal Kothari

Vishnu S. Chipade, Abhishek, Mangal Kothari et al.

This paper discusses the conceptual design and proof-of-concept flight demonstration of a novel variable pitch quadrotor biplane Unmanned Aerial Vehicle concept for payload delivery. The proposed design combines vertical takeoff and landing (VTOL), precise hover capabilities of a quadrotor helicopter and high range, endurance and high forward cruise speed characteristics of a fixed wing aircraft. The proposed UAV is designed for a mission requirement of carrying and delivering 6 kg payload to a destination at 16 km from the point of origin. First, the design of proprotors is carried out using a physics based modified Blade Element Momentum Theory (BEMT) analysis, which is validated using experimental data generated for the purpose. Proprotors have conflicting requirement for optimal hover and forward flight performance. Next, the biplane wings are designed using simple lifting line theory. The airframe design is followed by power plant selection and transmission design. Finally, weight estimation is carried out to complete the design process. The proprotor design with 24 deg preset angle and -24 deg twist is designed based on 70% weightage to forward flight and 30% weightage to hovering flight conditions. The operating RPM of the proprotors is reduced from 3200 during hover to 2000 during forward flight to ensure optimal performance during cruise flight. The estimated power consumption during forward flight mode is 64% less than that required for hover, establishing the benefit of this hybrid concept. A proof-of-concept scaled prototype is fabricated using commercial-off-the-shelf parts. A PID controller is developed and implemented on the PixHawk board to enable stable hovering flight and attitude tracking.

Animesh Kumar Shastry, Mangal Kothari

This work develops a unified optimal control framework for a Quadrotor Biplane tailsitter UAV capable of operating seamlessly across hover, transition, and cruise flight regimes. Although the tailsitter configuration enables mechanically simple mode switching, the transition maneuver remains challenging due to strong nonlinearities and rapidly varying aerodynamics. To address this, a trajectory optimization scheme based on nonlinear programming with direct collocation is formulated, incorporating nonlinear dynamics, actuator limits, and angle-of-attack constraints. The resulting optimal trajectories are safe, reliable, and time-efficient. For the cruise-to-hover maneuver, optimal trajectories are generated over a range of initial cruise velocities and subsequently learned using feedforward multilayer neural networks. The learned model generalizes across operating conditions and enables real-time generation of constraint-satisfying transition trajectories. These trajectories provide both feedforward control inputs and reference state profiles, which are tracked using a Model Predictive Controller (MPC). The MPC eliminates the need for controller switching or gain scheduling across flight envelopes, enabling a single universal controller for hover, transition, and cruise. A nonlinear Dynamic Inversion (DI) controller is also designed for comparison. Two numerical schemes for MPC are implemented and evaluated. Simulation results across all flight modes demonstrate that MPC achieves superior robustness to parameter uncertainties compared to DI. A computational cost analysis further highlights the trade-off between execution time and performance for the different MPC solvers.

Jitu Sanwale, Mangal Kothari, Hari B. Hablani et al.

This paper presents a physics-consistent digital twin framework for end-to-end modeling and evaluation of Global Navigation Satellite Systems (GNSS) user receiver equipment. In contrast to conventional GNSS simulations that rely on predefined signal models, the proposed framework enforces dynamic consistency between satellite ephemerides, user motion, and received signal observables through trajectory-driven injection of code-phase and Doppler dynamics. The GPS L1 C/A signal is synthesized in accordance with the IS-GPS-200 Rev. N specification, with motion-induced effects derived directly from orbital and user kinematics, and augmented by ionospheric and tropospheric delay models. The resulting complex baseband signal is converted to radio frequency using a software-defined radio platform disciplined by an external reference clock, enabling seamless hardware-in-the-loop integration with commercial and software receivers. Validation across static, moderate-motion, and high-dynamics scenarios, including projectile-like trajectories, demonstrates close agreement between truth-model and receiver-estimated code phase, Doppler, and position, as well as strong correspondence between simulated and measured intermediate frequency spectra. The results establish the proposed digital twin as a high-fidelity, repeatable, and physically consistent platform for GNSS receiver evaluation, tracking-loop stress testing, and development of robust navigation algorithms.

Namrata Gupta, Mangal Kothari, Abhishek

This paper carries out the mathematical modeling, simulation, and control law design for a quadrotor with variable-pitch propellers. The use of variable-pitch propeller for thrust variation instead of RPM regulation facilitates generation of negative thrust, thereby augmenting the rate of change of thrust generation amenable for aggressive maneuvering. Blade element theory along with momentum theory is used to estimate propeller thrust and torque essential for formulating equation of motion of the vehicle. The proposed flight dynamics model is used for non-linear control design using dynamic inversion technique, which is then used to stabilize, track reference trajectory, and simulate flip maneuver. The rotor torque is an irrational function of the control input which makes the control design challenging. To address this problem, the control design employs three loops. The outer loop solves the translational dynamics to generate the thrust, pitch angle, and roll angle commands required to track the prescribed trajectory. Using the command generated in the outer loop, the inner loop simplifies the rotational dynamics to provide the desired rate of angular velocities. A control allocation loop is added to address the problem of nonlinearity associated with rotor torque. This is done by introducing the derivative of thrust coefficient as a virtual control input. These virtual inputs determine the derivatives of thrust and body moments, which in turn is used to generate the required thrust and body moments. The concept is validated by showing attitude stabilization in real flight for a variable pitch quadrotor. The performance of the proposed design is shown through simulated results for attitude stabilization and trajectory following. Reverse thrust capability of variable-pitch quadrotor is also shown by performing flip maneuver in which quadrotor roll angle changes from 0 to 180 degrees.

Nidhish Raj, Ravi N. Banavar, Abhishek et al.

We consider the problem of attitude tracking for small-scale aerobatic helicopters. A small scale helicopter has two subsystems: the fuselage, modeled as a rigid body; and the rotor, modeled as a first order system. Due to the coupling between rotor and fuselage, the complete system does not inherit the structure of a simple mechanical system. The coupled rotor fuselage dynamics is first transformed to rigid body attitude tracking problem with a first order actuator dynamics. The proposed controller is developed using geometric and backstepping control technique. The controller is globally defined on $SO(3)$ and is shown to be locally exponentially stable. The controller is validated in simulation and experiment for a 10 kg class small scale flybarless helicopter by demonstrating aggressive roll attitude tracking.

Nidhish Raj, Ravi N Banavar, Abhishek et al.

This paper highlights the significance of the rotor dynamics in control design for small-scale aerobatic helicopters, and proposes two singularity free robust attitude tracking controllers based on the available states for feedback. 1. The first, employs the angular velocity and the flap angle states (a variable that is not easy to measure) and uses a backstepping technique to design a robust compensator (BRC) to \textbf{\textit{actively}} suppress the disturbance induced tracking error. 2. The second exploits the inherent damping present in the helicopter dynamics leading to a structure preserving, \textbf{\textit{passively}} robust controller (SPR), which is free of angular velocity and flap angle feedback. The BRC controller is designed to be robust in the presence of two types of uncertainties: structured and unstructured. The structured disturbance is due to uncertainty in the rotor parameters, and the unstructured perturbation is modeled as an exogenous torque acting on the fuselage. The performance of the controller is demonstrated in the presence of both types of disturbances through numerical simulations. In contrast, the SPR tracking controller is derived such that the tracking error dynamics inherits the natural damping characteristic of the helicopter. The SPR controller is shown to be almost globally asymptotically stable and its performance is evaluated experimentally by performing aggressive flip maneuvers. Throughout the study, a nonlinear coupled rotor-fuselage helicopter model with first order flap dynamics is used.

Prateek Priyaranjan Pradhan, Ketan Rajawat, Mangal Kothari

Communication-aware trajectory generation for unmanned aerial vehicles (UAVs) operating in urban environments requires simultaneous consideration of vehicle dynamics, wireless communication quality, obstacle avoidance, and onboard energy limitations. In such missions, UAVs must navigate through obstacle-rich environments while ensuring reliable relay of mission-critical sensory information to ground infrastructure. This results in a highly nonlinear and nonconvex optimal control problem involving coupled communication and flight-dynamics constraints. This paper presents a communication-constrained energy-optimal trajectory generation framework for quadrotor UAVs operating in urban environments. The proposed formulation incorporates full rigid-body quadrotor dynamics, urban wireless communication models, cumulative data throughput constraints, and obstacle avoidance requirements within a unified free-final-time optimal control framework. Unlike conventional approaches based on simplified kinematic or point-mass models, the proposed framework generates dynamically feasible trajectories suitable for practical aerial platforms. The resulting nonconvex optimal control problem is solved iteratively using sequential convex programming (SCP). Numerical simulations for multiple urban mission scenarios demonstrate the ability of the proposed framework to generate energy-efficient and communication-aware trajectories while adapting mission duration according to data relay requirements. The proposed methodology provides a practical framework for autonomous UAV operations requiring reliable communication in dense urban environments.

Mahathi Bhargavapuri, Soumya Ranjan Sahoo, Mangal Kothari

The topological obstructions on the attitude space of a rigid body make global asymptotic stabilization impossible using continuous state-feedback. This paper presents novel algorithms to overcome such topological limitations and achieve arbitrary attitude maneuvers with only continuous, memory-less state-feedback. We first present nonlinear control laws using both rotation matrices and quaternions that give rise to one almost globally asymptotically stabilizable equilibrium along with a nowhere dense set of unstable equilibria. The unstable equilibria are uniquely identified in the attitude error space. Pseudo-targets are then designed to make the controller believe that the attitude error is within the region of attraction of the stable equilibrium. Further, the pseudo-target ensures that maximum control action is provided to push the closed-loop system toward the stable equilibrium. The proposed algorithms are validated using both numerical simulations and experiments to show their simplicity and effectiveness.

Nitik Jain, Mangal Kothari

Reliable detection of humans beneath forest canopy remains a difficult remote-sensing challenge due to sparse, structured, and viewpoint-dependent occlusion. This paper presents a multimodal proof-of-concept pipeline that integrates three complementary approaches: (i) experimental evaluation of LiDAR returns through vegetation to assess the feasibility of active sensing, (ii) visible--thermal image fusion using a multi-scale transform and sparse-representation framework to enhance human saliency, and (iii) synthetic-aperture image formation via Airborne Optical Sectioning (AOS) to suppress canopy clutter. A YOLOv5 detector is fine-tuned on the Teledyne FLIR thermal dataset and evaluated on thermal and fused imagery. Results show that the tested terrestrial LiDAR configuration provides limited penetration for object-level detection, while visible--thermal fusion improves target visibility in low-contrast scenes and AOS enhances ground-plane detection in synthetic forest imagery. The fine-tuned YOLOv5 achieves a mean average precision of $\sim$0.83 on the top three FLIR classes. These findings establish an initial baseline for UAV-deployable search-and-rescue and surveillance systems operating in forested environments, and motivate future work on dedicated forest datasets and real-time multimodal integration.

Akhil B Krishna, Mangal Kothari

This paper extends the Model Predictive Static Programming (MPSP) framework for nonlinear systems evolving on Euclidean spaces to simple mechanical systems evolving on Lie groups. Classical optimal control approaches based on Pontryagin's Maximum Principle (PMP) lead to nonlinear two-point boundary value problems (TPBVPs), whose numerical solution becomes particularly challenging on nonlinear configuration spaces. To overcome this difficulty, the proposed Lie-group MPSP framework reformulates the finite-horizon optimal control problem as a sequence of static quadratic programs that admit closed-form control updates, thereby avoiding the need to solve TPBVPs directly. The development relies on left-trivialized variations, intrinsic linearization on Lie groups, and a recursive computation of terminal sensitivity matrices, which together enable computationally efficient real-time implementation. The proposed method is demonstrated through optimal flipping maneuvers of a variable-pitch quadrotor (VPQ) and a single-main-rotor helicopter (SMRH), both of which are capable of generating negative thrust. For validation, continuous-time necessary and sufficient optimality conditions are derived, and the corresponding TPBVP solutions are compared against the trajectories generated by the proposed MPSP method in numerical simulations. In addition, the proposed algorithm is systematically compared with the iterative Linear Quadratic Regulator (iLQR) method, and a detailed numerical study is presented to highlight the relative performance and computational features of the two approaches.

Aryan Sharma, Nitik Jain, Mangal Kothari

In this work, we present and evaluate a method to perform real-time multiple drone detection and three-dimensional localization using state-of-the-art tiny-YOLOv4 object detection algorithm and stereo triangulation. Our computer vision approach eliminates the need for computationally expensive stereo matching algorithms, thereby significantly reducing the memory footprint and making it deployable on embedded systems. Our drone detection system is highly modular (with support for various detection algorithms) and capable of identifying multiple drones in a system, with real-time detection accuracy of up to 77\% with an average FPS of 332 (on Nvidia Titan Xp). We also test the complete pipeline in AirSim environment, detecting drones at a maximum distance of 8 meters, with a mean error of $23\%$ of the distance. We also release the source code for the project, with pre-trained models and the curated synthetic stereo dataset.

Akash Jain, Manish Kumar, Rithvik Patibandla et al.

Anahita is an autonomous underwater vehicle which is currently being developed by interdisciplinary team of students at Indian Institute of Technology(IIT) Kanpur with aim to provide a platform for research in AUV to undergraduate students. This is the second vehicle which is being designed by AUV-IITK team to participate in 6th NIOT-SAVe competition organized by the National Institute of Ocean Technology, Chennai. The Vehicle has been completely redesigned with the major improvements in modularity and ease of access of all the components, keeping the design very compact and efficient. New advancements in the vehicle include, power distribution system and monitoring system. The sensors include the inertial measurement units (IMU), hydrophone array, a depth sensor, and two RGB cameras. The current vehicle features hot swappable battery pods giving a huge advantage over the previous vehicle, for longer runtime.

Hardik Parwana, Mangal Kothari

The attitude space has been parameterized in various ways for practical purposes. Different representations gain preferences over others based on their intuitive understanding, ease of implementation, formulaic simplicity, and physical as well as mathematical complications involved in using them. This technical note gives a brief overview and discusses the quaternions, which are fourth dimensional extended complex numbers and used to represent orientation. Their relationship to other modes of attitude representation such as Euler angles and Axis-Angle representation is also explored and conversion from one representation to another is explained. The conventions, intuitive understanding and formulas most frequently used and indispensable to any quaternion application are stated and wherever possible, derived.