Hemjyoti Das

Hemjyoti Das

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publications

A comparative study between a cant angle hexacopter and a conventional hexacopter

Published in International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT), 2016

The purpose of this paper is to present a brief comparison between a conventional hexacopter and a cant angle hexacopter. A conventional hexacopter has got all its 6 rotors fixed and thrusted upwards in the body frame which gives it a decoupled 4 DOF motion or a coupled 6 DOF motion. But a cant angle hexacopter has all its six rotors canted at an angle tangentially to the radius of the frame. It provides 2 extra degree of freedom in the translational X & Y axis without any coupling. A conventional hexacopter cannot translate in X & Y axis without tilting but the cant angle hexacopter serves this purpose. In this paper we compare their dynamic models using classical Newton Euler equations and design a PD controller for simulating the vehicle dynamics.

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Static performance analysis of electric propulsion system in quadrotors

Published in International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT), 2016

This paper describes the selection of brushless motors, propellers and battery for getting maximum time of hover for a quadrotor UAV. We also introduce a experimental testbed to measure various parameters of the system like torque, thrust, RPM, current and voltage. The static testbed is directly interfaced through MATLAB for real time data acquisition. We tested different motor and propeller combinations to find the relation of their various parameters with efficiency and static coefficients.

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Experimental Implementation of Fuzzy Vision-Based Tracking Control of Quad-Rotor

Published in Soft Computing Applications: Proceedings of the 7th International Workshop Soft Computing Applications, 2017

This paper presents a novel approach to detect and track an object using a quadrotor-UAV. The proposed system mainly consists of two parts- (i) Object detection and tracking using histogram backprojection and CAMSHIFT tracker, (ii) Fuzzy Proportional and Fuzzy Proportional-Derivative controller for controlling the drone. We implemented our algorithm using ROS (Robot Operating System), OPENCV library and MATLAB programming environment.

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Bio-inspired Landing of Quadrotor using Improved State Estimation

Published in IFAC-PapersOnLine, 2018

This paper presents an improved state estimation technique - a fusion of Monocular SLAM (Simultaneous Localization and Mapping) and INS (Inertial Navigation System). It is utilized in landing a commercially available low cost quadrotor (Parrot AR Drone 2.0) in indoor environments along a trajectory generated by a bio-inspired guidance method. The method is based on Tau theory and facilitates safe and smooth landing of UAVs by closing motion gaps with zero relative velocity and acceleration. A depth camera (Microsoft Kinect) provides a helping hand in very accurate landing towards the end of the quadrotor’s trajectory. A dynamic inversion based controller is designed which works as a outer loop controller for the quadrotor.

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Dynamic inversion control of quadrotor with a suspended load

Published in IFAC-PapersOnLine, 2018

In this paper, I have tackled the problem of a quadrotor with a suspended load using nonlinear dynamic inversion method. The main purpose of this paper is to present a new dynamics of the UAV-load system using Newton’s law. I applied dynamic inversion control for directing the UAV to the desired coordinates and simultaneously minimizing the sway angle of the suspended mass. I have carried the entire simulation in the inertial frame. My approach is to use an outer loop controller for maintaining the position and an inner loop controller for the desired roll, pitch and yaw rate. I have performed the simulations on MATLAB.

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Incremental Nonlinear Dynamic Inversion Control of Long-Stroke Pneumatic Actuators

Published in European Control Conference (ECC), 2021

Pneumatic cylinders provide an environment-friendly actuation means by minimizing the leakage of any harmful industrial fluids, as occurs for hydraulic actuators. However, pneumatic actuation has not been utilized widely for industrial servo applications due to its highly nonlinear nature. Incremental nonlinear dynamic inversion (INDI) is a form of nonlinear dynamic inversion (NDI) that relies less on plant-model information, and is thus inherently robust to mismatches in the known plant-model, and also to external disturbances. Developing an incremental nonlinear controller for a pneumatic system is the main focus of this research article, which is accomplished by utilizing a cascaded-control approach, where the inner-loop INDI tracks a given force and the outer-loop NDI is for controlling the piston-position. Moreover, realistic sensor noises have been added in the simulation and the robustness of the incremental approach is demonstrated with respect to a baseline PID controller.

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Motor-level N-MPC for cooperative active perception with multiple heterogeneous UAVs

Published in IEEE Robotics and Automation Letters, 2022

This letter introduces a cooperative control framework based on Nonlinear Model Predictive Control (NMPC) for solving an Active Information Acquisition problem (AIA) using a system of multiple multirotor UAVs equipped with onboard sensors. The observation task of the NMPC is a minimum-uncertainty pose estimation of a moving feature which is observed by the multi-UAV system, using a cooperative Kalman filter. The controller considers a full nonlinear model of the multirotors – including the motor-level actuation units and their real constraints in terms of maximum torque – and embeds the Kalman filter estimation uncertainty in its prediction. The framework allows and exploits heterogeneity in the actuation and sensing systems by considering a generic model of UAV – including both quadrotors and tilted-propeller multirotors – and a generic model of range-and-bearing sensor with arbitrary rate and field of view. The capability of the proposed framework to reduce the cooperative estimation uncertainty of a static or a moving feature, thus leading the system to optimal sensing configurations, is demonstrated through Gazebo simulations and real experiments. The software is provided open-source.

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Nonlinear model predictive control for human-robot handover with application to the aerial case

Published in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022

In this article, we consider the problem of delivering an object to a human coworker by means of an aerial robot (AR). To this aim, we present an ergonomics-aware Nonlinear Model Predictive Control (NMPC) designed to autonomously perform the handover. The method is general enough to be applied to any multi-rotor aerial vehicle (MRAV) with a minimal adaptation of the robot model. The formulation of the optimal control problem steers the AR toward a handover location by optimizing the human coworker ergonomics, which includes the predicted arm joint torques of the human. The motion task is expressed in a frame relative to the human, whose motion model is included in the equations of the NMPC. This allows the controller to promptly adapt to the human movements by predicting her future poses over the horizon. The control framework also accounts for the problem of maintaining visibility on the human coworker, while respecting both the actuation and state limits of the robot. Additionally, a safety barrier is embedded in the controller to avoid any risk of collision with the human partner. Realistic simulations are performed to validate the feasibility of the approach and the source code of the implementation is released open-source.

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Hardware-in-the-Loop Simulation of Vehicle-Manipulator Systems for Physical Interaction Tasks

Published in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023

Hardware-in-the-loop simulation (HILS) allows a more realistic evaluation of control approaches than what is possible with pure software simulations, but without the actual complexity of the complete system. This is important for some complex systems such as orbital robots, where testing of the system is typically not possible after its launch, and an on-ground replica is used to validate the performance of such a system. In this article, an impedance-matching approach is presented to match the end-effector dynamics of a fixed-base robot manipulator with that of a target vehicle-manipulator system (VMS), while taking into account the redundant nullspace dynamics in a connected real-time simulation framework. This approach ensures that the forces and torques exerted by the system on the environment matches with that of the simulated system. The contact wrenches used in our approach are not obtained from numerical simulations, but rather from real physical interaction, which is one of the main advantages of our approach. The effectiveness of our method is validated by demonstrating various physical interaction tasks with the environment, using a suspended aerial manipulator as the target system.

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Observer-based Controller Design for Oscillation Damping of a Novel Suspended Underactuated Aerial Platform

Published in IEEE International Conference on Robotics and Automation (ICRA), 2024

In this work, we present a novel actuation strategy for a suspended aerial platform. By utilizing an underactuation approach, we demonstrate the successful oscillation damping of the proposed platform, modeled as a spherical double pendulum. A state estimator is designed in order to obtain the deflection angles of the platform, which uses only onboard IMU measurements. The state estimator is an extended Kalman filter (EKF) with intermittent measurements obtained at different frequencies. An optimal state feedback controller and a PD+ controller are designed in order to dampen the oscillations of the platform in the joint space and task space respectively. The proposed underactuated platform is found to be more energy-efficient than an omnidirectional platform and requires fewer actuators. The effectiveness of our proposed system is validated using both simulations and experimental studies

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Whole-Body Stabilization of a Cable-Suspended Multirotor Platform Carrying a Slung Load

Published in IEEE Transactions on Automation Science and Engineering (T-ASE), 2025

Suspended multirotor platforms are fascinating systems that can be employed in construction applications to provide safe transportation of heavy loads. Such a system comprising a cable-suspended platform with attached load features seven degrees of freedom (DoF) motion for the whole system. In this paper, we propose a composite whole-body control framework for the stabilization of the suspended multirotor platform system, leveraging singular perturbation theory to exploit the inherent three time-scale dynamics of the system. The control strategy computes the underactuated 3-DoF wrench space generated by the platform’s actuation units for the stabilization of the complete system. Building upon this, we develop a superposition-based shared control approach and then compare the two controllers. Moreover, to address specific cases where the time-scale separation between two dynamics of the triple-spherical pendulum becomes negligible, we design an operational space controller. The control approaches are validated using both extensive numerical simulations and experiments in different scenarios. We also carried out numerical robustness and stability analysis of the whole system. Note that our system relies on only onboard sensors for state estimation, which makes it effective for real-life outdoor applications.

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Learning Swing-up Maneuvers for a Suspended Aerial Manipulation Platform in a Hierarchical Control Framework

Published in IFAC-PapersOnLine, 2025

In this work, we present a novel approach to augment a model-based control method with a reinforcement learning (RL) agent and demonstrate a swing-up maneuver with a suspended aerial manipulation platform. These platforms are targeted towards a wide range of applications on construction sites involving cranes, with swing-up maneuvers allowing it to perch at a given location, inaccessible with purely the thrust force of the platform. Our proposed approach is based on a hierarchical control framework, which allows different tasks to be executed according to their assigned priorities. An RL agent is then subsequently utilized to adjust the reference set-point of the lower-priority tasks to perform the swing-up maneuver, which is confined in the nullspace of the higher-priority tasks, such as maintaining a specific orientation and position of the end-effector. Our approach is validated using extensive numerical simulation studies.

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Partial Feedback Linearization Control of a Cable-Suspended Multirotor Platform for Stabilization of an Attached Load

Published in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2025

In this work, we present a novel control approach based on partial feedback linearization (PFL) for the stabilization of a suspended aerial platform with an attached load. Such systems are envisioned for various applications in construction sites involving cranes, such as the holding and transportation of heavy objects. Our proposed control approach considers the underactuation of the whole system while utilizing its coupled dynamics for stabilization. We demonstrate using numerical stability analysis that these coupled terms are crucial for the stabilization of the complete system. We also carried out robustness analysis of the proposed approach in the presence of external wind disturbances, sensor noise, and uncertainties in system dynamics. As our envisioned target application involves cranes in outdoor construction sites, our control approaches rely on only onboard sensors, thus making it suitable for such applications. We carried out extensive simulation studies and experimental tests to validate our proposed control approach.

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Energy-based Swing-up and Grasping Maneuver using Suspended Aerial Manipulator

Published in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2026

In this work, we demonstrate a swing-up and grasping maneuver for the suspended-aerial manipulation platform. The swing-up motion of the platform is envisioned for target applications where its propulsion units cannot generate sufficient thrust to reach a desired pose. An energy regulation approach is employed to drive the suspended aerial manipulator platform to the desired limit cycle. Once the periodic oscillations are achieved, the designed online motion generator commands the manipulator to approach and grasp the given target. In this work, we employ a control strategy in which the controllers for the aerial platform and the manipulator are designed independently, while considering the dynamic coupling between the two subsystems. Our proposed approach relies on onboard sensors and a camera-tracking system, and is validated through extensive simulation studies and experimental tests.

talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

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