Whereas the transport of matter by wheeled vehicles or legged robots can be guaranteed in engineered landscapes such as roads or rails, locomotion prediction in complex environments such as collapsed buildings or crop fields remains challenging. Inspired by the principles of information transmission, which allow signals to be reliably transmitted over "noisy" channels, we developed a "matter-transport" framework that demonstrates that noninertial locomotion can be provably generated over noisy rugose landscapes (heterogeneities on the scale of locomotor dimensions). Experiments confirm that sufficient spatial redundancy in the form of serially connected legged robots leads to reliable transport on such terrain without requiring sensing and control. Further analogies from communication theory coupled with advances in gaits (coding) and sensor-based feedback control (error detection and correction) can lead to agile locomotion in complex terradynamic regimes.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1126/science.ade4985 | DOI Listing |
Sensors (Basel)
January 2025
Department of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada.
This paper presents a comprehensive approach to evaluating the ability of multi-legged robots to traverse confined and geometrically complex unstructured environments. The proposed approach utilizes advanced point cloud processing techniques integrating voxel-filtered cloud, boundary and mesh generation, and dynamic traversability analysis to enhance the robot's terrain perception and navigation. The proposed framework was validated through rigorous simulation and experimental testing with humanoid robots, showcasing the potential of the proposed approach for use in applications/environments characterized by complex environmental features (navigation inside collapsed buildings).
View Article and Find Full Text PDFSci Rep
January 2025
Department of Robotics, Graduate School of Engineering, Tohoku University, Sendai, 980-8579, Japan.
Four-legged robots are becoming increasingly pivotal in navigating challenging environments, such as construction sites and disaster zones. While substantial progress in robotic mobility has been achieved using reinforcement learning techniques, quadruped animals exhibit superior agility by employing fundamentally different strategies. Bio-inspired controllers have been developed to replicate and understand biological locomotion strategies.
View Article and Find Full Text PDFISA Trans
December 2024
Robotic Research Laboratory, Centre of Excellence in Experimental Solid Mechanics and Dynamics, School of Mechanical Engineering, Iran University of Science and Technology, Tehran 16846-13114, Iran.
In this paper, trajectory tracking control as the pursuit of a specific target by wheel-legged mobile robots (WLMRs) in an environment with the presence of obstacles is presented. These types of robots are designed to navigate different paths such as slippery trajectories, paths with obstacles, and other challenging paths. In addition, the robot can move its legs in different surface conditions and operate more flexibly with the help of wheels attached to the legs.
View Article and Find Full Text PDFEur Urol Open Sci
January 2025
The Research Center for Age-Related Functional Decline and Disease, Innlandet Hospital Trust, Ottestad, Norway.
Sci Rep
December 2024
Department of Mechanical Engineering, Tarbiat Modares University, Tehran, Iran.
In this scholarly investigation, the study focuses on scrutinizing the locomotion and control mechanisms governing a single-legged robot. The analysis encompasses the robot's movement dynamics pertaining to two primary objectives: executing jumps and sustaining equilibrium throughout successive jump sequences. Diverse concepts of this robot model have been scrutinized, leading to the introduction of a distinctive semi-active model devised for maintaining the robot's balance.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!