Bhatt, M., Zhen, H., Kennedy III, M., & Mehr, N. (2024). Understanding and Imitating Human-Robot Motion with Restricted Visual Fields. arXiv preprint arXiv:2410.05547.
This research paper investigates the importance of considering limited visual fields in human-robot interaction, aiming to develop a robotic system that can accurately predict and imitate human motion in environments with obstacles.
The researchers developed a robotic agent with a restricted field of view and range, simulating human visual limitations. They collected human trajectory data from a custom-designed game environment where participants navigated a robot with a limited field of view towards a goal while avoiding obstacles. Using this data, they trained a diffusion model to learn and imitate human navigation strategies, considering both observation limitations and motion policies. The model's performance was evaluated in simulations and a real-world experiment with a physical car.
The study found that incorporating observation limitations, such as field of view and object detection probability, significantly improved the accuracy of predicting and imitating human motion. The trained diffusion model successfully replicated human-like navigation behavior in both simulated and real-world environments, demonstrating the feasibility of learning from human demonstrations with restricted perception.
The authors conclude that accurately modeling human perception limitations, particularly restricted visual fields, is crucial for developing robots that can effectively interact and collaborate with humans in shared environments. By considering these limitations, robots can better anticipate human actions and adapt their behavior accordingly.
This research contributes to the field of human-robot interaction by highlighting the importance of incorporating realistic perceptual models in robot design. The proposed approach has the potential to enhance the safety and efficiency of human-robot collaboration in various domains, including manufacturing, healthcare, and domestic assistance.
The study primarily focused on visual perception limitations. Future research could explore the impact of other sensory limitations, such as auditory or tactile, on human-robot interaction. Additionally, investigating the generalization of the proposed approach to more complex and dynamic environments with multiple agents would be valuable.
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