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Trajectory Planning for a Six Axis Manipulator for SFF-Inspired Depth Estimation


  • Faculty of Manipal Institute of Technology, Manipal University, Manipal - 576104, Karnataka, India
  • Department of Mechatronics Engineering, SRM University, Kattankulathur - 603203, Tamil Nadu, India
  • Division of Mechatronics, Department of Production Technology, MIT Campus, Anna University, Chennai-600025, Tamil Nadu, India


Objectives: Trajectory planning is the most vital procedure in every continuous path control based application of robotic arm type manipulators. This paper presents the methodology adopted for planning a trajectory required to be followed by the eye-in-hand camera mounted near the end-effector of a six axis manipulator. The basic purpose is to acquire a sequence of images by translating the camera along the optical axis of the camera which is meant to be used by an algorithm inspired by Shape from Focus (SFF). Methods/Statistical Analysis: The movement of the camera (the end effector) is controlled in the task space of the robot a Cartesian space approach is presented where-in the inverse kinematics computations needs to be performed at run time. All the trajectory planning and simulation of the robot’s movements are demonstrated in the simulation where the cues for camera motion are obtained from the SFF-inspired algorithm. Since the SFF-inspired algorithm requires a linear trajectory to be followed by the camera and manipulator is an all-revolute joint based one, careful understanding of the workspace of the robot for singularities is of prime importance. The ability of the manipulator to orient in three axes at the various reachable positions of the workspace is estimated by a manipulability measure. The linear trajectory to be followed by the end-effector is planned in the region of the workspace which has the highest manipulability. Findings: The paper describes the various steps involved in the process of understanding the manipulability of the workspace and planning of the trajectory in accordance with the manipulability index. The details of the trajectory planning to meet the requirements are clearly illustrated. Application/Improvements: Though the intended purpose of planning the trajectory is specific to a computer vision task, the methodology demonstrated is applicable for any application involving linear trajectories. The scope for future work in continuation of the current work is in the direction of dynamics affected trajectory planning.


Linear Trajectory, Manipulability, SFF, Trajectory Planning.

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