Impact of Anthropomorphic Robot Design on Trust and Attention in Industrial Human-Robot Interaction

The application of anthropomorphic features to robots is generally considered beneficial for human-robot interaction (HRI ). Although previous research has mainly focused on social robots, the phenomenon gains increasing attention in industrial human-Robot interaction as well. In this study, the impact of anthropomorphic design of a collaborative industrial robot on the dynamics of trust and visual attention allocation was examined. Participants interacted with a robot, which was either anthropomorphically or non-anthropomorphically designed. Unexpectedly, attribute-based trust measures revealed no beneficial effect of anthropomorphism but even a negative impact on the perceived reliability of the robot. Trust behavior was not significantly affected by an anthropomorphic robot design during faultless interactions, but showed a relatively steeper decrease after participants experienced a failure of the robot. With regard to attention allocation, the study clearly reveals a distracting effect of anthropomorphic robot design. The results emphasize that anthropomorphism might not be an appropriate feature in industrial HRI as it not only failed to reveal positive effects on trust, but distracted participants from relevant task areas which might be a significant drawback with regard to occupational safety in HRI.

Optimizing Cycle Time of Industrial Robotic Tasks with Multiple Feasible Configurations at the Working Points

Industrial robot applications should be designed to allow the robot to provide the best performance for increasing throughput. In this regard, both trajectory and task order optimization are crucial, since they can heavily impact cycle time. Moreover, it is very common for a robotic application to be kinematically or functionally redundant so that multiple arm configurations may fulfill the same task at the working points. In this context, even if the working cycle is composed of a small number of points, the number of possible sequences can be very high, so that the robot programmer usually cannot evaluate them all to obtain the shortest possible cycle time. One of the most well-known problems used to define the optimal task order is the Travelling Salesman Problem (TSP), but in its original formulation, it does not allow to consider different robot configurations at the same working point. This paper aims at overcoming TSP limitations by adding some mathematical and conceptual constraints to the problem. With such improvements, TSP can be used successfully to optimize the cycle time of industrial robotic tasks where multiple configurations are allowed at the working points. Simulation and experimental results are presented to assess how cost (cycle time) and computational time are influenced by the proposed implementation.

Improved Routing Protocol Based on Multiobjective Optimization in Industrial Robot Networks

This paper decomposes the routing process of industrial robot network using the application of analytic hierarchy process in decision-making. The influence of four factors, such as path length, data integrity, energy consumption, and receiving delay, on routing effect is analyzed. Simultaneous interpreting routes are selected to achieve the purpose of routing. Simulation results show that this method can more comprehensively consider the factors affecting routing and is superior to the existing methods in terms of energy consumption, data integrity, and transmission delay.

Do Speed and Proximity Affect Human-Robot Collaboration with an Industrial Robot Arm?

Current guidelines for Human-Robot Collaboration (HRC) allow a person to be within the working area of an industrial robot arm whilst maintaining their physical safety. However, research into increasing automation and social robotics have shown that attributes in the robot, such as speed and proximity setting, can influence a person’s workload and trust. Despite this, studies into how an industrial robot arm’s attributes affect a person during HRC are limited and require further development. Therefore, a study was proposed to assess the impact of robot’s speed and proximity setting on a person’s workload and trust during an HRC task. Eighty-three participants from Cranfield University and the ASK Centre, BAE Systems Samlesbury, completed a task in collaboration with a UR5 industrial robot arm running at different speeds and proximity settings, workload and trust were measured after each run. Workload was found to be positively related to speed but not significantly related to proximity setting. Significant interaction was not found for trust with speed or proximity setting. This study showed that even when operating within current safety guidelines, an industrial robot can affect a person’s workload. The lack of significant interaction with trust was attributed to the robot’s relatively small size and high success rate, and therefore may have an influence in larger industrial robots. As workload and trust can have a significant impact on a person’s performance and satisfaction, it is key to understand this relationship early in the development and design of collaborative work cells to ensure safe and high productivity.