Task-Trajectory Analysis Package in the Robot Operating System
For many manufacturing tasks, such as welding and cutting, the task trajectory, or path, is known a priori in the object's reference frame. What is not known is whether or not the robot can reach the entirety of the trajectory given the relative location of the object frame to the robot's base frame and its reachable and/or dexterous workspace. The problem increases in complexity with each additional object in the robot's workspace. Some robots need to perform tasks in cluttered or confined environments, such as a glovebox, and the ability to know if and where the manipulator can perform a certain task is crucial for both design and operation. This thesis describes the development, design, and implementation of a Task-Trajectory Analysis Package (T-TAP) within the Robot Operating System (ROS) framework.
Reachability has been extensively discussed in the literature, but current reachability visualization tools do not account for task data, and instead describe the robot's global workspace and thus take a long time to compute. Such tools may be useful for designing robotic systems, but their value diminishes when analyzing a specific task and environment. T-TAP focuses on the task space and is capable of producing real-time or near real-time feedback about the validity of a path. The results are shown in an easy-to-interpret visualization of the path points and their relative quality as measured using selected performance metrics.
T-TAP contains several capabilities. The first, and simplest, validates reachability for discrete points along the trajectory. An inverse kinematic (IK) solver is used to plan from one trajectory point to the next. The user can use standard ROS IK solvers or utilize their own IK solver. Next, T-TAP uses the Jacobian to analyze the system's performance as it completes the proposed trajectory. It ensures that joint and velocity limits are not violated, singularities are avoided, and is extensible to include additional user-defined performance metrics.
T-TAP requires no prior computations, is hardware agnostic, and can be run entirely in simulation. It can reduce the time required to place and plan a trajectory by an order of magnitude. It is designed to work seamlessly with existing ROS path-planning packages. The operator needs only to send the path to T-TAP and T-TAP will analyze the trajectory. This information will allow the operator to intelligently adjust the path so that it is reachable and viable.