Synchronisation and Differentiation: Two Stages of Coordinative Structure

While motor skill acquisition process is regarded as development of coordination, typically regarded as synchronisation among joint movements, we found another phenomenon which we call differentiation as a consequence of synchronisation. The synchronised movement established is decomposed into several sections or modulated to be executed on different timings without breaking the coordination among them, resulting in the gain of efficiency or flexibility. In the acquisition of skills, the coordinative structure thus goes through two stages: synchronisation and differentiation. We verify in this paper our observation through our experiments and dynamical analysis of the kneading of ceramic art and playing the shaker in samba

Climbing and Walking Robots

With the advancement of technology, new exciting approaches enable us to render mobile robotic systems more versatile, robust and cost-efficient. Some researchers combine climbing and walking techniques with a modular approach, a reconfigurable approach, or a swarm approach to realize novel prototypes as flexible mobile robotic platforms featuring all necessary locomotion capabilities. The purpose of this book is to provide an overview of the latest wide-range achievements in climbing and walking robotic technology to researchers, scientists, and engineers throughout the world. Different aspects including control simulation, locomotion realization, methodology, and system integration are presented from the scientific and from the technical point of view. This book consists of two main parts, one dealing with walking robots, the second with climbing robots. The content is also grouped by theoretical research and applicative realization. Every chapter offers a considerable amount of interesting and useful information

Trajectory planning of jumping over an obstacle for one-legged jumping robot

For one-legged passive jumping robot, a trajectory planning strategy is developed to jump over an obstacle integrating three various dynamics among jumping process. Manipulability ellipsoids are effective tools to perform task space analysis and motion optimization of redundant manipulators. Jumping robot can be considered as a redundant manipulator with a load held at the end-effector. The concept of inertia matching ellipsoid and directional manipulability is extended to optimize the take-off posture of jumping robot, and the optimized results have been used to plan jumping trajectory. Aimed at the sensitivity of a trajectory to constraint conditions on point-to-point motion planning, the 6th order polynomial function is proposed to plan jumping motion having a better robustness to the parameters change of constraint conditions than traditional 5th order polynomial function. In order to lift the foot over the obstacle, correction functions are constructed under unchanged boundary constraint conditions. Furthermore, the body posture is controlled based on internal motion dynamics and steady-state consecutive jumping motion principle. A prototype model is designed, and the effectiveness of the proposed method is confirmed via simulations performed on parameters of designed prototype

Rajaplaneerimine multi-robot süsteemile jagatud lasti transportimisel

Shared payload transportation has emerged as one of the key real-world applications that warrants the deployment of multiple robots. The key motivation stems from the fact that actuation and sensing abilities of multiple robots can be pooled together to transport objects that are either too big or heavy to be handled by a single robot. This thesis proposes algorithmic and software frameworks to achieve precise multi-robot coordination for object transportation. On the algorithmic side, a trajectory optimization formulation is developed which generates collision-free and smooth trajectories for the robots transporting the object. State-of-the art Gradient Descent variants are utilized for obtaining the solution. On the software side, a trajectory planner (local planner) is developed and integrated to Robot Operating System (ROS). The local planner is responsible for calculating individual velocities for any number of robots forming a rigid geometric in-plane constellation. Extensive simulation as well as real-world experiments are performed to demonstrate the validity of the developed solutions. It is demonstrated that how the proposed trajectory optimization approach outperforms off-the-shelf planners with respect to metrics like smoothness and collision avoidance. In estonian: Ühise lasti transportimine mitme roboti poolt on kujunenud üheks rakendusvaldkonnaks, kus mitme roboti samaaegne kasutamine on õigustatud. Mitme roboti andureid ja ajameid on eriti kasulik kasutada transportimaks objekte, mis on ühe roboti jaoks kas liiga suured ja/või rasked. Käesolev lõputöö pakub välja algoritmilise ja tarkvaralise raamistiku, mis võimaldab täpselt koordineerida mitme roboti koostööd ühise lasti liigutamisel. Välja on töötatud trajektooride optimeerimise algoritm, mis genereerib kokkupõrkevabad ja sujuvad ühist objekti kandvate robotite trajektoorid. Selleks on kasutatud nüüdisaegset gradientlaskumise (ingl Gradient Descent) meetodit. Tarkvara poolelt on loodud trajektoori planeerija (lokaalne planeerija) ja see on integreeritud arendusplatvormil ROS (Robot Operating System). Lokaalne planeerija arvutab individuaalsed kiirused igale robotile, mis moodustavad ühise jäiga tasapinnalise kujundi, kusjuures robotite arv kujundis ei ole piiratud. Väljatöötatud lahenduse toimimist on kontrollitud ulatuslike simulatsioonide abil aga ka viies läbi praktilisi katseid. Väljapakutud trajektoori optimeerimise lahendus ületab olemasolevaid planeerijaidd nii trajektoori sujuvuse kui ka kokkupõrgete vältimise võime osas

Bio-Inspired Robotics

Modern robotic technologies have enabled robots to operate in a variety of unstructured and dynamically-changing environments, in addition to traditional structured environments. Robots have, thus, become an important element in our everyday lives. One key approach to develop such intelligent and autonomous robots is to draw inspiration from biological systems. Biological structure, mechanisms, and underlying principles have the potential to provide new ideas to support the improvement of conventional robotic designs and control. Such biological principles usually originate from animal or even plant models, for robots, which can sense, think, walk, swim, crawl, jump or even fly. Thus, it is believed that these bio-inspired methods are becoming increasingly important in the face of complex applications. Bio-inspired robotics is leading to the study of innovative structures and computing with sensory–motor coordination and learning to achieve intelligence, flexibility, stability, and adaptation for emergent robotic applications, such as manipulation, learning, and control. This Special Issue invites original papers of innovative ideas and concepts, new discoveries and improvements, and novel applications and business models relevant to the selected topics of ``Bio-Inspired Robotics''. Bio-Inspired Robotics is a broad topic and an ongoing expanding field. This Special Issue collates 30 papers that address some of the important challenges and opportunities in this broad and expanding field

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available