Context inference, localization and mapping in indoor environments using Mmwaves.

Abstract

Humanoid robots are among the most recognizable robotic systems in exploration, industrial applications, and personal assistance. However, like all bipedal systems, the main challenge that faces humanoid locomotion is stability. Humanoids are vulnerable to balance disturbances. The risks of humanoid falling are not limited to the robots but also affect the humans around them. The research efforts in humanoid stability in the past few decades have been far from shy, but there is still a long path before full stability is reached. This thesis presents biomimetic techniques for humanoid fall avoidance and gait design. The main two problems addressed in this thesis are push recovery during quiet standing and stability during walking. The proposed push recovery strategy is inspired by human reliance on three main sensory information to assess their posture: visual, vestibular, and somatosensory. Fusing sensory inputs enables the robot to adapt to different environmental changes during locomotion. Experimental results show improvements in maximum joint-torque exertion of up to 17.5percent and response time by 9.3percent. Inspired by excessive human reliance on somatosensory information, a model-free push recovery strategy is also developed enabling small-scale commercial humanoids to make use of foot pressure sensors to reject disturbances from any direction and at any location on the body. The proposed strategy withstands around 8.0percent higher magnitude push disturbances compared to standard control methods. On a related note, kinesiologists define the energy-exchange theory as the main guidance for human walking. In this thesis, an energy-exchange gait generation technique is developed through formulating an optimization problem capable of maintaining this human-inspired property. Additionally, a new Energy-Based Controller is developed to drive the generated energy-exchange gait. The new controller not only maintains the desired gait angles but also is more efficient in terms of energy expenditure and torque exertion on the joint