Topic
Humanoid robot
About: Humanoid robot is a research topic. Over the lifetime, 14387 publications have been published within this topic receiving 243674 citations. The topic is also known as: 🤖.
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TL;DR: The so-called DEAs are introduced emphasizing the key points of working principle, key components and electromechanical modeling approaches, and different DEA-driven soft robots, including wearable/humanoid robots, walking/serpentine robots, flying robots and swimming robots, are reviewed.
Abstract: Conventional industrial robots with the rigid actuation technology have made great progress for humans in the fields of automation assembly and manufacturing. With an increasing number of robots needing to interact with humans and unstructured environments, there is a need for soft robots capable of sustaining large deformation while inducing little pressure or damage when maneuvering through confined spaces. The emergence of soft robotics offers the prospect of applying soft actuators as artificial muscles in robots, replacing traditional rigid actuators. Dielectric elastomer actuators (DEAs) are recognized as one of the most promising soft actuation technologies due to the facts that: i) dielectric elastomers are kind of soft, motion-generating materials that resemble natural muscle of humans in terms of force, strain (displacement per unit length or area) and actuation pressure/density; ii) dielectric elastomers can produce large voltage-induced deformation. In this survey, we first introduce the so-called DEAs emphasizing the key points of working principle, key components and electromechanical modeling approaches. Then, different DEA-driven soft robots, including wearable/humanoid robots, walking/serpentine robots, flying robots and swimming robots, are reviewed. Lastly, we summarize the challenges and opportunities for the further studies in terms of mechanism design, dynamics modeling and autonomous control.
301 citations
28 Apr 2008
TL;DR: A Unified Framework for Whole-Body Humanoid Robot Control with Multiple Constraints and Contacts for Robots in Dynamic Environments.
Abstract: Adaptive Multiple Resources Consumption Control for an Autonomous Rover.- Adaptive Snake Robot Locomotion: A Benchmarking Facility for Experiments.- Architecture for Neuronal Cell Control of a Mobile Robot.- The Ares Robot: Case Study of an Affordable Service Robot.- Balancing the Information Gain Against the Movement Cost for Multi-robot Frontier Exploration.- Compiling POMDP Models for a Multimodal Service Robot from Background Knowledge.- Constraint Based Object State Modeling.- A COTS-Based Mini Unmanned Aerial Vehicle (SR-H3) for Security, Environmental Monitoring and Surveillance Operations: Design and Test.- Eyes-Neck Coordination Using Chaos.- Formation Graphs and Decentralized Formation Control of Multi Vehicles with Kinematics Constraints.- Global Urban Localization of an Outdoor Mobile Robot with Genetic Algorithms.- Grip Force Control Using Vision-Based Tactile Sensor for Dexterous Handling.- HNG: A Robust Architecture for Mobile Robots Systems.- Information Relative Map Going Toward Constant Time SLAM.- Measuring Motion Expressiveness in Wheeled Mobile Robots.- Modeling, Simulation and Control of Pneumatic Jumping Robot.- Multilayer Perceptron Adaptive Dynamic Control of Mobile Robots: Experimental Validation.- Path Planning and Tracking Control for an Automatic Parking Assist System.- Performance Evaluation of Ultrasonic Arc Map Processing Techniques by Active Snake Contours.- Planning Robust Landmarks for Sensor Based Motion.- Postural Control on a Quadruped Robot Using Lateral Tilt: A Dynamical System Approach.- Propose of a Benchmark for Pole Climbing Robots.- Rat's Life: A Cognitive Robotics Benchmark.- Reactive Trajectory Deformation to Navigate Dynamic Environments.- Recovery in Autonomous Robot Swarms.- Robot Force/Position Tracking on a Surface of Unknown Orientation.- Scalable Operators for Feature Extraction on 3-D Data.- Semi-autonomous Learning of an RFID Sensor Model for Mobile Robot Self-localization.- A Simple Visual Navigation System with Convergence Property.- Stability of On-Line and On-Board Evolving of Adaptive Collective Behavior.- A Unified Framework for Whole-Body Humanoid Robot Control with Multiple Constraints and Contacts.- Visual Approaches for Handle Recognition.- Visual Top-Down Attention Framework for Robots in Dynamic Environments.- Visual Topological Mapping.- 3D Mapping and Localization Using Leveled Map Accelerated ICP.
301 citations
29 Oct 2001
TL;DR: This paper investigates inverse kinematics learning for resolved motion rate control (RMRC) employing an optimization criterion to resolve kinematic redundancies and demonstrates how a recently developed statistical learning algorithm, locally weighted projection regression, allows efficient learning of inverse k Cinematic mappings in an incremental fashion even when input spaces become rather high dimensional.
Abstract: Real-time control of the end-effector of a humanoid robot in external coordinates requires computationally efficient solutions of the inverse kinematics problem. In this context, this paper investigates inverse kinematics learning for resolved motion rate control (RMRC) employing an optimization criterion to resolve kinematic redundancies. Our learning approach is based on the key observations that learning an inverse of a nonuniquely invertible function can be accomplished by augmenting the input representation to the inverse model and by using a spatially localized learning approach. We apply this strategy to inverse kinematics learning and demonstrate how a recently developed statistical learning algorithm, locally weighted projection regression, allows efficient learning of inverse kinematic mappings in an incremental fashion even when input spaces become rather high dimensional. Our results are illustrated with a 30-DOF humanoid robot.
300 citations
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TL;DR: The future promises lots of robots in the authors' everyday lives; some, perhaps many, of them could look and behave like people but only if being humanoid represents a technological advantage over their relatively utilitarian counterparts.
Abstract: The future promises lots of robots in our everyday lives; some, perhaps many, of them could look and behave like people but only if being humanoid represents a technological advantage over their relatively utilitarian counterparts.
294 citations
02 Mar 2006
TL;DR: This work used hierarchical statistical mediation analysis to trace differences in people's mental model of robots from these choices to identify the causal path from the robot's voice and head dimensions to the participants' mental model, and to their willingness to follow the robots' advice.
Abstract: Humanoid robots offer many physical design choices such as voice frequency and head dimensions We used hierarchical statistical mediation analysis to trace differences in people's mental model of robots from these choices In an experiment, a humanoid robot gave participants online advice about their health We used mediation analysis to identify the causal path from the robot's voice and head dimensions to the participants' mental model, and to their willingness to follow the robot's advice The male robot voice predicted impressions of a knowledgeable robot, whose advice participants said they would follow Increasing the voice's fundamental frequency reduced this effect The robot's short chin length (but not its forehead dimensions) predicted impressions of a sociable robot, which also predicted intentions to take the robot's advice We discuss the use of this approach for designing robots for different roles, when people's mental model of the robot matters
293 citations