In humanoid robotics, there is a long pursuit of making bipeds capable of walking in highly unstructured and roughly sensed environments. Within this goal, our objective is to develop a compliant bipedal humanoid robot, based on McKibben pneumatic actuators that can move in these terrains as well as quickly adapt to unpredicted variations on the contact state. We present here the first part of our work, focusing on the design, construction and control of a pneumatic robotic joint capable of achieving the control performance necessary for responding compliantly and accurately to contact transitions while delivering high forces needed to handle the physical challenges associated with rough terrains. In particular, we address our progress in the mechanical and embedded electronic design, actuator modeling, and compliant control strategies for a robotic joint based on fluidic pneumatic artificial muscles (PAMs). The proposed robotic joint has been validated experimentally, exploring various aspects of its performance as well as its shortcomings, but overall demonstrating the potential benefits of using pneumatic muscles. / text

In order to operate safely and naturally in human-centered environments, robots need to respond compliantly to force and contact interactions. While advanced robotic torsos and arms have been built that successfully achieve this, a somewhat neglected research area is the construction of compliant wheeled mobile bases. This thesis describes the mechatronics behind Trikey, a holonomic wheeled mobile base employing torque sensing at each of its three omni wheels so that it can detect and respond gracefully to force interactions. Trikey's mechanical design, kinematic and dynamic models, and control architecture are described, as well as simple experiments demonstrating compliant control. Trikey is designed to support a force-controlled humanoid upper body, and eventually, the two will be controlled together using whole-body control algorithms that utilize the external and internal dynamics of the entire system. / text

This study investigates if preferences for mental capacities in robots vary across different application domains and identifies influential factors, both in individuals’ characteristics and attributes specific to each robot domain. Employing a between-subject design, participants (N=271) completed a survey collecting both quantitative and qualitative data on preferences for 12 mental capacities across six robot types situated in a specific application domain (medicine, defense, household, social, education, customer service). Half of the mental capacities align with each dimension (experience and agency) in the two-dimensional model of mind (Gray et al., 2007; McMurtrie, 2023). Key findings reveal a general preference for high agency ability and low experience ability across all application domains. Exceptions were found in preference for lower agency ability in the cleaning robot and higher experience ability in the companion robot. Qualitative analysis indicates a desire for objective and logical robots functioning without emotions, while demonstrating empathy for human emotions. Additionally, gender and educational background emerged as factors influencing preference for lower experience abilities in robots. While previous research has mainly focused on attribution of mental capacities to technical agents, this study provides insights into human preferences and factors affecting them. These insights can guide responsible and ethics-driven development and design of robot technology within the field of human-robot interaction.