Assessing the Role of Gaze Tracking in Optimizing Humans-In-The-Loop Telerobotic Operation Using Multimodal Feedback

A key challenge in achieving effective robot teleoperation is minimizing teleoperators’ cognitive workload and fatigue. We set out to investigate the extent to which gaze tracking data can reveal how teleoperators interact with a system. In this study, we present an analysis of gaze tracking, captured as participants completed a multi-stage task: grasping and emptying the contents of a jar into a container. The task was repeated with different combinations of visual, haptic, and verbal feedback. Our aim was to determine if teleoperation workload can be inferred by combining the gaze duration, fixation count, task completion time, and complexity of robot motion (measured as the sum of robot joint steps) at different stages of the task. Visual information of the robot workspace was captured using four cameras, positioned to capture the robot workspace from different angles. These camera views (aerial, right, eye-level, and left) were displayed through four quadrants (top-left, top-right, bottom-left, and bottom-right quadrants) of participants’ video feedback computer screen, respectively. We found that the gaze duration and the fixation count were highly dependent on the stage of the task and the feedback scenario utilized. The results revealed that combining feedback modalities reduced the cognitive workload (inferred by investigating the correlation between gaze duration, fixation count, task completion time, success or failure of task completion, and robot gripper trajectories), particularly in the task stages that require more precision. There was a significant positive correlation between gaze duration and complexity of robot joint movements. Participants’ gaze outside the areas of interest (distractions) was not influenced by feedback scenarios. A learning effect was observed in the use of the controller for all participants as they repeated the task with different feedback combination scenarios. To design a system for teleoperation, applicable in healthcare, we found that the analysis of teleoperators’ gaze can help understand how teleoperators interact with the system, hence making it possible to develop the system from the teleoperators’ stand point.

Towards Tethered Tool Manipulation Planning with the Help of a Tool Balancer

Handling and maneuvering tools across a robot workspace is a challenging task that often requires the implementation of constrained motion planning. In the case of wired or tethered tools, their maneuvering becomes considerably harder by the tool cable. If the cable presence is not considered, the robot motions may make the cable become entangled with the robot arms or elements of its workspace, causing accidents or unnecessary strain on the robot and the tool. Furthermore, the behavior of the tool cable during manipulation and its degree of entanglement around the robot are difficult to predict. The present paper introduces a constrained manipulation planner for dual-armed tethered tool manipulation involving tool re-grasping. Our solution employs a tool balancer to straighten the tool cable and facilitate the cable deformation problem. The planner predicts the cable states during manipulation and restricts the robot motions in order to avoid cable entanglements and collisions while performing tool re-posing tasks. Furthermore, the planner also applies orientational constraints to limit the cable bending, reducing the torque and stress suffered by the robot due to the cable tension. Simulations and real-world experiments validated the presented method.

Enhancing Energy Efficiency of a 4-DOF Parallel Robot Through Task-Related Analysis

Enhancing energy efficiency is one of the main challenges of today’s industrial robotics and manufacturing technology. In this paper a task-related analysis of the energetic performance of a 4-DOF industrial parallel robot is presented, and the optimal location of a predefined task with respect to the robot workspace is investigated. An optimal position of the task relative to the robot can indeed reduce the actuators’ effort and the energy consumption required to complete the considered operation. The dynamic and electro-mechanical models of the manipulators are developed and implemented to estimate the energy consumption of a parametrized motion with trapezoidal speed profile, i.e., a pick-and-place operation. Numerical results provide energy consumption maps that can be adopted to place the starting and ending points of the task in the more energy-efficient location within the robot workspace.