In this paper forward kinematic analysis and differential motion analysis of the KUKA KR 16 Industrial Robotic System has been considered, which is a 6 d.o.f articulated robotic manipulator but we have calculated and shown spatial trajectory only 5 d.o.f, due to critical trajectory planning of D-H implementation. Forward kinematic analysis uses D-H formulation, Differential motion uses Jacobians also determines angular positions and end-effector‟s translational angular velocity at each point of its trajectory in the cartesian co-ordinates respectively. A trajectory passing through initial point, lift off point, set down point and final point is interpolated in the joint space using cubic splines. The trajectory scheme assumes two more intermediate points on trajectory. Thus, there are five segments of the entire trajectory. A LABVIEW source code is developed to obtain all the kinematics parameters and important conclusions have been observed from the values obtained.

Robot, Forward Kinematics, Jacobians, D-H matrix, Trajectory Planing

[1]. Z. Chen, K. Jiang, and J.C. Hung. Local observability matrix and its application to observability analyses. In Industrial Electronics
Society, 16th Annual Conference of IEEE, Nov. 2018.
[2]. A. Chilian, H. Hirschmuller, and M. G ¨ orner. Multi- ¨ sensor data fusion for robust pose estimation of a sixlegged walking robot. In
Intelligent Robots and Systems, IEEE/RSJ International Conference on, Sep. 2018.
[3]. S. Chitta, P. Vernaza, R. Geykhman, and D.D. Lee. Proprioceptive localization for a quadrupedal robot on known terrain. In Robotics and Automation, IEEE International Conference on, Apr. 2017.
[4]. J. A. Cobano, J. Estremera, and P. Gonzalez de Santos. Location of legged robots in outdoor environments. Robotics and Autonomous
Systems, 56:751– 761, 2016.
[5]. N. El-Sheimy, Haiying Hou, and Xiaoji Niu. Analysis and modeling of inertial sensors using allan variance. Instrumentation and
Measurement, IEEE Transactions on, 57(1):140–149, Jan. 2015.
[6]. B. Gassmann, F. Zacharias, J.M. Zollner, and R. Dill- ¨ mann. Localization of walking robots. In Robotics and Automation, IEEE Int. Conf. on, Apr. 2014.
[7]. O. Gur and U. Saranli. Model-based proprioceptive state estimation for spring-mass running. In Proceedings of Robotics: Science and
Systems, Jun. 2014.
[8]. R. Hermann and A. Krener. Nonlinear controllability and observability. Automatic Control, IEEE Transactions on, 22(5):728–740, Oct.
2014.
[9]. G.P. Huang, A.I. Mourikis, and S.I. Roumeliotis. Analysis and improvement of the consistency of extended kalman filter based slam. In Robotics and Automation, IEEE International Conference on, May 2013.
[10]. Guoquan P. Huang, Anastasios I. Mourikis, and Stergios I. Roumeliotis. Observability-based rules for designing consistent ekf slam estimators. International Journal of Robotics Research, 29:502–528, Apr. 2013.
[11]. M. Hutter, C. Gehring, M. Bloesch, M.A. Hoepflinger, C.D. Remy, and R. Siegwart. StarlETH: A compliant quadrupedal robot for fast, efficient, and versatile locomotion. In Climbing and Walking Robots, International Conference on, Jul. 2012.
[12]. S.J. Julier and J.K. Uhlmann. A counter example to the theory of simultaneous localization and map building. In Robotics and
Automation, IEEE Int. Conf. on, May 2011
[13]. P.C. Lin, H. Komsuoglu, and D.E. Koditschek. A leg configuration measurement system for full-body pose estimates in a hexapod robot. Robotics, IEEE Transactions on, 21(3):41–422, Jun. 2009.
[14]. P.C. Lin, H. Komsuoglu, and D.E. Koditschek. Sensor data fusion for body state estimation in a hexapod robot with dynamical gaits. Robotics, IEEE Transactions on, 22(5):932–943, Oct. 2006.
[15]. International Journal of Scientific Research in Computer Sciences and Engineering (ISSN: 2320-7639) [16] International Journal of Scientific Research in Network Security and Communication (ISSN: 2321-3256)