The IEEE International Conference on Advanced Robotics and Mechatronics (ICARM) is the flagship conference of both IEEE-SMC TC on Bio-mechatronics and Bio-robotics Systems, and IEEE-RAS TC on NeuroRobotics Systems. ICARM 2022 took place in the Steigenberger Hotel, Guilin, China from July 9th to 11th, 2022. ULTRACEPT researchers Qinbing Fu, Xuelong Sun and Tian Liu attended this event with their co-authored paper titled: “Efficient bio-robotic estimation of visual dynamic complexity”.
Qinbing presented “Efficient bio-robotic estimation of visual dynamic complexity” in the regular session of the conference. This presentation gave a great introduction and demonstration of our multimodal swarm robotics platform named VColCOSP, which appealed to our academic peers who share similar researcher interests.
Abstract
Visual dynamic complexity is ubiquitous, hidden attribute of the visual world that every motion-sensitive vision system is faced with. However, it is implicit and intractable which has never been quantitatively described due to difficulty in defending temporal features correlated to spatial image complexity. Learning from biological visual processing, we propose a novel bio-robotic approach to estimate visual dynamic complexity, effectively and efficiently, which can be used as a new metric for assessing dynamic vision systems implemented in robots. Here we apply a bio-inspired neural network model to quantitatively estimate such complexity associated with spatial-temporal frequency of moving visual scene. The model is implemented in an autonomous micro-mobile robot navigating freely in an arena encompassed by visual walls displaying moving scenes. The response of the embedded visual module can make reasonable prediction on surrounding dynamic complexity since it can be mapped monotonically to varying moving frequencies of visual scene. The experiments demonstrate this “predictor” is effective against different visual scenarios that can be established as a new metric for assessing visual systems. To prove its viability, we utilise it to investigate the performance boundary of a collision detection visual system in changing environment with increasing dynamic complexity.
The conference provided the ULTRACEPT researchers an opportunity to network and participate in knowledge exchange with researchers from other universities and academic institutions, including leading experts and professors in this field, paving the way for potential research cooperation in the future.
In this event, the ULTRACEPT group listened to high quality plenary talks relevant with our group’s topics. Xuelong said “the ideas presented by the speakers cover many aspects of the cutting-edge technologies of AI and autonomous robots such as swarm intelligence, embodiment, cognitive, etc.”. The group had an impressive experience and grasped some interesting and useful ideas and inspirations for future studies.
