3,174 research outputs found
A Robust Model Predictive Control Approach for Autonomous Underwater Vehicles Operating in a Constrained workspace
This paper presents a novel Nonlinear Model Predictive Control (NMPC) scheme
for underwater robotic vehicles operating in a constrained workspace including
static obstacles. The purpose of the controller is to guide the vehicle towards
specific way points. Various limitations such as: obstacles, workspace
boundary, thruster saturation and predefined desired upper bound of the vehicle
velocity are captured as state and input constraints and are guaranteed during
the control design. The proposed scheme incorporates the full dynamics of the
vehicle in which the ocean currents are also involved. Hence, the control
inputs calculated by the proposed scheme are formulated in a way that the
vehicle will exploit the ocean currents, when these are in favor of the
way-point tracking mission which results in reduced energy consumption by the
thrusters. The performance of the proposed control strategy is experimentally
verified using a Degrees of Freedom (DoF) underwater robotic vehicle inside
a constrained test tank with obstacles.Comment: IEEE International Conference on Robotics and Automation (ICRA-2018),
Accepte
Design and development of autonomous robotic fish for object detection and tracking
In this article, an autonomous robotic fish is designed for underwater operations like object detection and tracking along with collision avoidance. The computer-aided design model for prototype robotic fish is designed using the Solid Works® software to export an stereolithography (STL) file to MakerBot, a 3D printer, to manufacture the parts of robotic fish using polylactic acid thermoplastic polymer. The precise maneuverability of the robotic fish is achieved by the propulsion of a caudal fin. The oscillation of the caudal fin is controlled by a servomotor. A combination of visual and ultrasonic sensors is used to track the position and distance of the desired object with respect to the fish and also to avoid the obstacles. The robotic fish has the ability to detect an object up to a distance of 90 cm at normal exposure conditions. A computational fluid dynamics analysis is conducted to analyze the fluid hydrodynamics (flow rate of water and pressure) around the hull of a robotic fish and the drag force acting on it. A series of experimental results have shown the effectiveness of the designed underwater robotic fish. </jats:p
Underwater Vehicles
For the latest twenty to thirty years, a significant number of AUVs has been created for the solving of wide spectrum of scientific and applied tasks of ocean development and research. For the short time period the AUVs have shown the efficiency at performance of complex search and inspection works and opened a number of new important applications. Initially the information about AUVs had mainly review-advertising character but now more attention is paid to practical achievements, problems and systems technologies. AUVs are losing their prototype status and have become a fully operational, reliable and effective tool and modern multi-purpose AUVs represent the new class of underwater robotic objects with inherent tasks and practical applications, particular features of technology, systems structure and functional properties
Aerospace Medicine and Biology: a Continuing Bibliography with Indexes (Supplement 328)
This bibliography lists 104 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during September, 1989. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance
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
A Comprehensive Review on Autonomous Navigation
The field of autonomous mobile robots has undergone dramatic advancements
over the past decades. Despite achieving important milestones, several
challenges are yet to be addressed. Aggregating the achievements of the robotic
community as survey papers is vital to keep the track of current
state-of-the-art and the challenges that must be tackled in the future. This
paper tries to provide a comprehensive review of autonomous mobile robots
covering topics such as sensor types, mobile robot platforms, simulation tools,
path planning and following, sensor fusion methods, obstacle avoidance, and
SLAM. The urge to present a survey paper is twofold. First, autonomous
navigation field evolves fast so writing survey papers regularly is crucial to
keep the research community well-aware of the current status of this field.
Second, deep learning methods have revolutionized many fields including
autonomous navigation. Therefore, it is necessary to give an appropriate
treatment of the role of deep learning in autonomous navigation as well which
is covered in this paper. Future works and research gaps will also be
discussed
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