Course

Introduction to traditional gradient based Optimization algorithms; Optimality criterion for unconstrained and constrained optimization problems Heuristic, Meta-heuristics, and Evolutionary algorithms: selective algorithms specific to robotic applications.

Spatial representation of a rigid body: Position – Rotational Matrix – Euler angles: problem formulation to find best Euler angles – Roll, Pitch and Yaw angles – Homogeneous transformation matrix, Finding optimal values of Roll, Pitch and Yaw. Kinematic Synthesis: Introduction- Type synthesis Dimensional Synthesis – Evolutionary method, Graph theory approach. Structural Optimization: Topology optimization – Dimensional synthesis using

optimization algorithms, Stiffness analysis and optimization.

Manipulator Kinematics: Introduction-Manipulator; Formulating objective function of the forward and inverse kinematics, identify optimum joint angle for the given position vector – Manipulator Jacobian: Finding optimum Jacobian of a manipulator. Path and Trajectory Planning: Introduction – Path Planning algorithms: Identifying optimal path using heuristic approach, Collision detection algorithms; Trajectory Planning: Algorithms, identifying optimum velocity and acceleration along the path.

Introduction to traditional gradient based Optimization algorithms; Optimality criterion for unconstrained and constrained optimization problems Heuristic, Meta-heuristics, and Evolutionary algorithms: selective algorithms specific to robotic applications.

Spatial representation of a rigid body: Position – Rotational Matrix – Euler angles: problem formulation to find best Euler angles – Roll, Pitch and Yaw angles – Homogeneous transformation matrix, Finding optimal values of Roll, Pitch and Yaw. Kinematic Synthesis: Introduction- Type synthesis Dimensional Synthesis – Evolutionary method, Graph theory approach. Structural Optimization: Topology optimization – Dimensional synthesis using

optimization algorithms, Stiffness analysis and optimization.

Manipulator Kinematics: Introduction-Manipulator; Formulating objective function of the forward and inverse kinematics, identify optimum joint angle for the given position vector – Manipulator Jacobian: Finding optimum Jacobian of a manipulator. Path and Trajectory Planning: Introduction – Path Planning algorithms: Identifying optimal path using heuristic approach, Collision detection algorithms; Trajectory Planning: Algorithms, identifying optimum velocity and acceleration along the path.

Course Outcomes:

CO1: Formulate Homogeneous Transformation Matrix (HTM) of rigid body and compute optimal values of Roll, Yaw and Pitch.

CO2: Develop solutions using optimization procedure for the forward kinematics and inverse kinematics of the robot manipulator.

CO3: Compute optimum path and trajectory of the robot using optimization methods.

CO4: Optimize the dimensions of the physical components of the robot using meta-heuristic approaches.

CO5: Identify an appropriate robot type with minimum dimensionality for a given specific task using optimization procedure.

Textbooks / References:

1.      Ghafil, Hazim Nasir, and Károly Jármai. Optimization for Robot Modelling with MATLAB. Springer International Publishing, 2020.

2.      Singiresu S Rao, “Engineering Optimization Theory and Practice”, 4th edition, John Wiley & Sons, Inc., 2009.

3.       Jha, Panchanand, and Bibhuti Bhusan Biswal. “Optimization Approach for Inverse Kinematic Solution.” In Kinematics. IntechOpen, 2017.