Insect-Inspired Body Size Learning Model on a Humanoid Robot

Arena, Paolo; Patané, Luca; Sanalitro, Dario; Vitanza, Alessandra

doi:10.1109/biorob.2018.8487635

Cited by 4 publications

(3 citation statements)

References 16 publications

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“…This function was found to be resident in a sub part of the CX, known as the protocerebral bridge. A computational model of this behavior was designed and implemented in a simulated hexapod robot [35], and finally tested using a humanoid robotic platform [278]. This proves that computationally relevant models, drawn from insect structure, can also be adopted for controlling different robotic bodies, not necessarily related to an insect-like biomimetic structure.…”

Section: Modelsmentioning

confidence: 87%

Insect-Inspired Robots: Bridging Biological and Artificial Systems

Manoonpong

Patané

Xiong

et al. 2021

Sensors

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This review article aims to address common research questions in hexapod robotics. How can we build intelligent autonomous hexapod robots that can exploit their biomechanics, morphology, and computational systems, to achieve autonomy, adaptability, and energy efficiency comparable to small living creatures, such as insects? Are insects good models for building such intelligent hexapod robots because they are the only animals with six legs? This review article is divided into three main sections to address these questions, as well as to assist roboticists in identifying relevant and future directions in the field of hexapod robotics over the next decade. After an introduction in section (1), the sections will respectively cover the following three key areas: (2) biomechanics focused on the design of smart legs; (3) locomotion control; and (4) high-level cognition control. These interconnected and interdependent areas are all crucial to improving the level of performance of hexapod robotics in terms of energy efficiency, terrain adaptability, autonomy, and operational range. We will also discuss how the next generation of bioroboticists will be able to transfer knowledge from biology to robotics and vice versa.

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Section: Modelsmentioning

confidence: 87%

Insect-Inspired Robots: Bridging Biological and Artificial Systems

Manoonpong

Patané

Xiong

et al. 2021

Sensors

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“…In 2017, Zhang et al designed a learning algorithm under OC mechanism, and with discrete motion spaces, a twowheeled robot learned the skill of self-balancing [10]. In 2018, Arena et al [11] proposed an insect-inspired body size learning algorithm, and adopted it to a humanoid robot and a control system who was composed of a series of layers developed using spiking neurons. The final processing layer was considered to be a gate to determine if an object is reachable or not depending on its estimated distance, and the correct decision was therefore learned through an operant conditioning method.…”

Section: ) Behaviorist Mechanismmentioning

confidence: 99%

Mobile Robot’s Sensorimotor Developmental Learning From Orientation and Curiosity

et al. 2020

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Simulating biological intelligence has been proved to be an effective way to design intelligent robots, and simultaneously can solve the problems existing in machine learning methods. For creatures, their motor skills achieving is the first stage of learning. By combining two important cognitive elements: orientation and curiosity, this paper proposes a new neurobiologically-inspired sensorimotor developmental learning method for the mobile robot. In this method, curiosity promotes robot's exploration of the environment, while orientation enhances robot's exploitation knowledge of the environment. The orientation cognitive algorithm is designed based on Skinner's operant conditioning theory, and its rationality is proved. The balance of exploration and exploitation, which is a key problem for all the cognitive learning method, is solved in this method. The developmental learning process can avoid fixed sensorimotor mapping space problem, and help reduce learning waste as well as computing waste. All of the developmental learning method's characters are finally verified via simulations on a virtual mobile robot.

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“…Further details on the mathematical description of the network and learning process can also be retrieved in Arena et al (2013a, 2018), where the proposed network was applied to learn the reachability space in roving and walking robots. In applying this control structure to HECTOR, we adopted the same paradigm for the network structure and the learning algorithm.…”

Section: Internal Models For Body-size Learningmentioning

confidence: 99%

Integrative Biomimetics of Autonomous Hexapedal Locomotion

et al. 2019

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Despite substantial advances in many different fields of neurorobotics in general, and biomimetic robots in particular, a key challenge is the integration of concepts: to collate and combine research on disparate and conceptually disjunct research areas in the neurosciences and engineering sciences. We claim that the development of suitable robotic integration platforms is of particular relevance to make such integration of concepts work in practice. Here, we provide an example for a hexapod robotic integration platform for autonomous locomotion. In a sequence of six focus sections dealing with aspects of intelligent, embodied motor control in insects and multipedal robots—ranging from compliant actuation, distributed proprioception and control of multiple legs, the formation of internal representations to the use of an internal body model—we introduce the walking robot HECTOR as a research platform for integrative biomimetics of hexapedal locomotion. Owing to its 18 highly sensorized, compliant actuators, light-weight exoskeleton, distributed and expandable hardware architecture, and an appropriate dynamic simulation framework, HECTOR offers many opportunities to integrate research effort across biomimetics research on actuation, sensory-motor feedback, inter-leg coordination, and cognitive abilities such as motion planning and learning of its own body size.

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Insect-Inspired Body Size Learning Model on a Humanoid Robot

Cited by 4 publications

References 16 publications

Insect-Inspired Robots: Bridging Biological and Artificial Systems

Insect-Inspired Robots: Bridging Biological and Artificial Systems

Mobile Robot’s Sensorimotor Developmental Learning From Orientation and Curiosity

Integrative Biomimetics of Autonomous Hexapedal Locomotion

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