Vođenje hodajućeg robota u strukturiranom prostoru zasnovano na računalnome vidu

Locomotion of a biped robot in a scenario with obstacles requires a high degree of coordination between perception and walking. This article presents key ideas of a vision-based strategy for guidance of walking robots in structured scenarios. Computer vision techniques are employed for reactive adaptation of step sequences allowing a robot to step over or upon or walk around obstacles. Highly accurate feedback information is achieved by a combination of line-based scene analysis and real-time feature tracking. The proposed vision-based approach was evaluated by experiments with a real humanoid robot.Lokomocija dvonožnog robota u prostoru s preprekama zahtijeva visoki stupanj koordinacije između percepcije i hodanja. U članku se opisuju ključne postavke strategije vođenja hodajućih robota zasnovane na računalnome vidu. Tehnike računalnoga vida primijenjene za reaktivnu adaptaciju slijeda koraka omogućuju robotu zaobilaženje prepreka, ali i njihovo prekoračivanje te penjanje na njih. Visoka točnost povratne informacije postignuta je kombinacijom analize linijskih segmenata u sceni i praćenjem značajki scene u stvarnome vremenu. Predloženi je sustav vođenja hodajućih robota eksperimentalno provjeren na stvarnome čovjekolikome robotu

Vođenje hodajućeg robota u strukturiranom prostoru zasnovano na računalnome vidu

Locomotion of a biped robot in a scenario with obstacles requires a high degree of coordination between perception and walking. This article presents key ideas of a vision-based strategy for guidance of walking robots in structured scenarios. Computer vision techniques are employed for reactive adaptation of step sequences allowing a robot to step over or upon or walk around obstacles. Highly accurate feedback information is achieved by a combination of line-based scene analysis and real-time feature tracking. The proposed vision-based approach was evaluated by experiments with a real humanoid robot.Lokomocija dvonožnog robota u prostoru s preprekama zahtijeva visoki stupanj koordinacije između percepcije i hodanja. U članku se opisuju ključne postavke strategije vođenja hodajućih robota zasnovane na računalnome vidu. Tehnike računalnoga vida primijenjene za reaktivnu adaptaciju slijeda koraka omogućuju robotu zaobilaženje prepreka, ali i njihovo prekoračivanje te penjanje na njih. Visoka točnost povratne informacije postignuta je kombinacijom analize linijskih segmenata u sceni i praćenjem značajki scene u stvarnome vremenu. Predloženi je sustav vođenja hodajućih robota eksperimentalno provjeren na stvarnome čovjekolikome robotu

Adaptive, fast walking in a biped robot under neuronal control and learning

Human walking is a dynamic, partly self-stabilizing process relying on the interaction of the biomechanical design with its neuronal control. The coordination of this process is a very difficult problem, and it has been suggested that it involves a hierarchy of levels, where the lower ones, e.g., interactions between muscles and the spinal cord, are largely autonomous, and where higher level control (e.g., cortical) arises only pointwise, as needed. This requires an architecture of several nested, sensori–motor loops where the walking process provides feedback signals to the walker's sensory systems, which can be used to coordinate its movements. To complicate the situation, at a maximal walking speed of more than four leg-lengths per second, the cycle period available to coordinate all these loops is rather short. In this study we present a planar biped robot, which uses the design principle of nested loops to combine the self-stabilizing properties of its biomechanical design with several levels of neuronal control. Specifically, we show how to adapt control by including online learning mechanisms based on simulated synaptic plasticity. This robot can walk with a high speed (> 3.0 leg length/s), self-adapting to minor disturbances, and reacting in a robust way to abruptly induced gait changes. At the same time, it can learn walking on different terrains, requiring only few learning experiences. This study shows that the tight coupling of physical with neuronal control, guided by sensory feedback from the walking pattern itself, combined with synaptic learning may be a way forward to better understand and solve coordination problems in other complex motor tasks

Towards a Theory Grounded Theory of Language

In this paper, we build upon the idea of theory grounding and propose one specific form of theory grounding, a theory of language. Theory grounding is the idea that we can imbue our embodied artificially intelligent systems with theories by modeling the way humans, and specifically young children, develop skills with theories. Modeling theory development promises to increase the conceptual and behavioral flexibility of these systems. An example of theory development in children is the social understanding referred to as “theory of mind.” Language is a natural task for theory grounding because it is vital in symbolic skills and apparently necessary in developing theories. Word learning, and specifically developing a concept of words, is proposed as the first step in a theory grounded theory of language