Sujit Rajappa

I am a Researcher at the Max Planck Institute for Biological Cybernetics in the group working with .

Currently, my research is devoted to

1) Design and development of novel Micro Aerial Vehicles(MAVs) with Titled Propellers.

2) Human-UAV Physical Interaction.

3) Robust Adaptive Attitude Controller in UAVs for Aggressive Manoeuvres.

4) External Force/Torque Wrench Observers for Aerial Vehicles.

Please refer the for details of the research topics.

Earlier, I worked as Control Systems Engineer at and Commissioning Engineer at in the (Gas To Liquid) Project.

My technical background includes but is not limited to

1) System Control Engineering

2) Industrial Process Automation

3) Robotics and Control

4) Unmanned Aerial Vehicles

1. A Novel Hexarotor UAV with Tilted Propellers

Mobility of a hexarotor UAV in its standard configuration are limited, since all the propeller force vectors are parallel and they achieve only 4 DoFs actuation, similar, e.g., to quadrotors. As a consequence, the hexarotor pose cannot track an arbitrary trajectory over time. In this project, we consider a different hexarotor architecture where propellers are tilted, without the need of any additional hardware. In this way, the hexarotor possess a 6~DoFs actuation which allows it to independently reach positions and orientations in free space and to be able to exert forces on the environment to resist any wrench for aerial manipulation tasks.

The main research focus are directed towards

1) Dynamic modelling of the novel tilted propeller hexarotor

2) Controllability and the tilt angle optimization for energy efficient flight

3) Non-linear control techniques for non-linear trajectory tracking

2. Towards Human-UAV Physical Interaction

Human-robot interaction is a field which is gaining increasing attention. However, current research is mostly limited to interaction with manipulator arms and ground robots. Unmanned Aerial Vehicles (UAV) are usually excluded with Human interaction research because they are considered dangerous and lack proper interaction surfaces to exchange forces. In this project, we  address the problem of Human-UAV physical interaction and we propose a straightforward approach to allow a human to intuitively command the UAV through exchanges of forces. Using a residual based estimator, we estimate the external forces and torques acting on the UAV. Through the employment of a sensor ring, we are able to separate the human interaction forces from additional disturbances as wind and parameter uncertainties. This knowledge is used inside a control framework where the human is allowed to change the desired trajectory by simply applying forces on the UAV. The main reaserch topics in this project

1) A feasible hardware architecture for the Human-UAV interaction

2) A methodology for the separation of the forces/torques applied by an interacting human from generic disturbances

3) A control framework which allows a human to provide intuitive force command to the UAV while the disturbances are rejected by the controller

3. Robust Adaptive Non-Linear Attitude Controller for UAVs

In this project, we develop a robust quadrotor controller for tracking a reference trajectory in presence of uncertainties and disturbances. An Adaptive Super Twisting controller is designed using the gain adaptation law, which has the advantage of not requiring the knowledge of the upper bound of the lumped uncertainties. The controller design is based on the regular form of the quadrotor dynamics, without separation in two nested control loops for position and attitude. The controller is  further extended by a feedforward dynamic inversion control that reduces the effort of the sliding mode controller. The Controller is tested in the presence of initial error, parameter uncertainties, noisy measurements and external perturbations.

4. An External Force/Torque Wrench Observer for Quadrotor UAVs

The fast and complex dynamics of UAVs are highly reactive to external disturbances. Consequently, outdoor flight, aerial manipulation and physical interaction with the environment become difficult tasks. Knowing the exact external force/torque disturbance wrench acting on an aerial vehicle could be of great importance. In this project, we consider a residual momenta-based external wrench estimator in a robo-centric approach. In this way, the estimation can be autonomously done onboard without relying on any extroceptive sensors, hence it is suitable for outdoor applications. The wrenches are observed using the Fault Detection and Isolation (FDI) technique. The research topic also invloves the application of the estimated wrench in different control techniques methodologies such as Near-Hovering Controller, Model Predicitive Control, etc.