RESUMEN
Human sensorimotor decision making has a tendency to get 'stuck in a rut', being biased towards selecting a previously implemented action structure (hysteresis). Existing explanations propose this is the consequence of an agent efficiently modifying an existing plan, rather than creating a new plan from scratch. Instead, we propose that hysteresis is an emergent property of a system learning from the consequences of its actions. To examine this, 152 participants moved a cursor to a target on a tablet device while avoiding an obstacle. Hysteresis was observed when the obstacle moved sequentially across the screen between trials, whereby the participant continued moving around the same side of the obstacle despite it now requiring a larger movement than the alternative. Two further experiments (n = 20) showed an attenuation when time and resource constraints were eased. We created a simple computational model capturing probabilistic estimate updating that showed the same patterns of results. This provides, to our knowledge, the first computational demonstration of how sensorimotor decision making can get 'stuck in a rut' through the updating of the probability estimates associated with actions.
RESUMEN
Introduction: Our work introduces a real-time robotic localization and mapping system for buried pipe networks. Methods: The system integrates non-vision-based exploration and navigation with an active-vision-based localization and topological mapping algorithm. This algorithm is selectively activated at topologically key locations, such as junctions. Non-vision-based sensors are employed to detect junctions, minimizing the use of visual data and limiting the number of images taken within junctions. Results: The primary aim is to provide an accurate and efficient mapping of the pipe network while ensuring real-time performance and reduced computational requirements. Discussion: Simulation results featuring robots with fully autonomous control in a virtual pipe network environment are presented. These simulations effectively demonstrate the feasibility of our approach in principle, offering a practical solution for mapping and localization in buried pipes.
RESUMEN
The development of future technologies can be highly influenced by our deeper understanding of the principles that underlie living organisms. The Living Machines conference aims at presenting (among others) the interdisciplinary work of behaving systems based on such principles. Celebrating the 10 years of the conference, we present the progress and future challenges of some of the key themes presented in the robotics workshop of the Living Machines conference. More specifically, in this perspective paper, we focus on the advances in the field of biomimetics and robotics for the creation of artificial systems that can robustly interact with their environment, ranging from tactile sensing, grasping, and manipulation to the creation of psychologically plausible agents.
