The world is slowly moving into increased human-robot interaction where both humans and robots can co-exist in the same domain. For the robot to be able to operate effectively in a man’s designed environment, it becomes necessary to model the robot with human capabilities as humans are seen as more capable. Replicating human becomes a huge challenge due to numerous degrees-of-freedom (DOFs) that human possess resulting into too many variables and nonlinear equations. Other challenges do occur like singularities.   In this thesis, the singularity challenge of a redundant humanoid arm is explored while maintaining a simple 7 DOF serial chain structure. As opposed to the 30 DOF human arm, a simpler 7 DOF humanoid arm is adopted and studied to eliminate the singularity challenges. The singularity problem mainly comes from the elbow and the spherical joints at the shoulder and wrist. A step-by-step review of available inverse kinematics techniques is made with more focus on the iterative Jacobian-based methods. A step-by-step approach is adopted so as to identify the source of singularities while using the iterative Jacobian-based techniques that are able to handle the nonlinearities of the equations.   The Singular Value Filtering (SVF) technique coupled with Selectively Damped Least Squares (SDLS) is employed. Without any restrictions to the stretch of the arm or end-effector pose, the method demonstrates, in conjunction with Euler angle singularity avoidance method, the elimination of singularity problems. This is achieved with no adjustment to kinematic model of the manipulator.