How to measure top-down influences in robotics?
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Measuring top-down influences in robotics involves various approaches outlined in the research papers. One method is through the simulation of top-down influences in visual attention mechanisms. Additionally, the use of top-down image processing algorithms with visual redundancies can help evaluate the performance of autonomous mobile robot systems. Another approach is the real-time assessment of human-robot trust using top-down depth camera tracking setups, which can detect signs of physical apprehension to infer changes in trust levels towards the robot. Furthermore, a top-down approach to expressing and implementing robotics algorithms can help reduce dependencies on lower-level details and facilitate the understanding and combination of different algorithmic variants. These methods collectively contribute to measuring and understanding the impact of top-down influences in robotics.
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| Papers (5) | Insight |
|---|---|
Open access•Journal Article | The paper proposes a top-down approach in robotics to manage algorithmic variability, shielding algorithms from lower-level details, facilitating comparison and combination of different algorithmic variants. |
08 Aug 2021 3 Citations | Top-down influences in robotics can be measured through real-time human-robot trust assessment using top-down visual tracking setups, observing signs of physical apprehension to infer changes in trust post-robot mistakes. |
07 Jul 1997 7 Citations | Top-down influences in robotics can be measured by evaluating the performance of visual subsystems with varying levels of redundancies to overcome noise effects, as shown in the simulation study. |
19 Dec 2009 3 Citations | The model in the paper measures top-down influences in robotics through learning object representations in long-term memory, deducing task-relevant features, estimating biases, mediating bottom-up and top-down processes, and object completion. |
| Top-down influences in robotics can be measured by assessing how linguistic cues impact anthropomorphism, expectations of capabilities, and moral regard for robots, as shown in the study. |
Related Questions
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