A Cockroach-Like Hexapod Robot for Natural Terrain Locomotion

1997 ◽  
Author(s):  
Randall D. Beer ◽  
Roger Quinn ◽  
Roy Ritzmann ◽  
Hillel Chiel
Keyword(s):  
Hexapod Robot ◽  
Natural Terrain

A Cockroach-Like Hexapod Robot for Natural Terrain Locomotion.

1998 ◽  
Author(s):  
Randall Beer ◽  
Roger Quinn ◽  
Roy Ritzmann ◽  
Hillel Chiel
Keyword(s):  
Hexapod Robot ◽  
Natural Terrain

FORMATION AND DEVELOPMENT OF THE NATURAL AND ECOLOGICAL FRAMEWORK OF THE TERRITORY OF BRYANSK TAKING INTO ACCOUNT THE INFLUENCE OF NATURAL TERRAIN

2019 ◽  
Vol 86 (6) ◽  
pp. 48-58
Author(s):  
L.A. VOLKOVA ◽  
◽  
V.V. ALEKSASHINA ◽  
A.A. TERESHINA ◽  
◽  
...  
Keyword(s):  
Ecological Framework ◽  
Natural Terrain

scholarly journals Getting grip in changing environments: the effect of friction anisotropy inversion on robot locomotion

2021 ◽  
Vol 127 (5) ◽  
Author(s):  
Halvor T. Tramsen ◽  
Lars Heepe ◽  
Jettanan Homchanthanakul ◽  
Florentin Wörgötter ◽  
Stanislav N. Gorb ◽  
...  
Keyword(s):  
Energy Efficient ◽  
Legged Locomotion ◽  
Hexapod Robot ◽  
Friction Anisotropy ◽  
Anisotropic Friction ◽  
Walking Behavior ◽  
Robot Locomotion ◽  
Computational Morphology ◽  
Anisotropic Structures ◽  
Walking Environment

AbstractLegged locomotion of robots can be greatly improved by bioinspired tribological structures and by applying the principles of computational morphology to achieve fast and energy-efficient walking. In a previous research, we mounted shark skin on the belly of a hexapod robot to show that the passive anisotropic friction properties of this structure enhance locomotion efficiency, resulting in a stronger grip on varying walking surfaces. This study builds upon these results by using a previously investigated sawtooth structure as a model surface on a legged robot to systematically examine the influences of different material and surface properties on the resulting friction coefficients and the walking behavior of the robot. By employing different surfaces and by varying the stiffness and orientation of the anisotropic structures, we conclude that with having prior knowledge about the walking environment in combination with the tribological properties of these structures, we can greatly improve the robot’s locomotion efficiency.

Behavior-Based Navigation of an Autonomous Hexapod Robot Using a Hybrid Automaton

2021 ◽  
Vol 102 (2) ◽  
Author(s):  
Mostafa Khazaee ◽  
Majid Sadedel ◽  
Atoosa Davarpanah
Keyword(s):  
Hexapod Robot ◽  
Hybrid Automaton ◽  
Behavior Based

scholarly journals Terrain classification and adaptive locomotion for a hexapod robot Qingzhui

2021 ◽  
Author(s):  
Yue Zhao ◽  
Feng Gao ◽  
Qiao Sun ◽  
Yunpeng Yin
Keyword(s):  
Legged Robots ◽  
Measurement Unit ◽  
Support Vector ◽  
Hexapod Robot ◽  
Terrain Classification ◽  
Adaptive Locomotion ◽  
Joint Torques ◽  
Active Compliance ◽  
Outdoor Environments ◽  
The Stability

AbstractLegged robots have potential advantages in mobility compared with wheeled robots in outdoor environments. The knowledge of various ground properties and adaptive locomotion based on different surface materials plays an important role in improving the stability of legged robots. A terrain classification and adaptive locomotion method for a hexapod robot named Qingzhui is proposed in this paper. First, a force-based terrain classification method is suggested. Ground contact force is calculated by collecting joint torques and inertial measurement unit information. Ground substrates are classified with the feature vector extracted from the collected data using the support vector machine algorithm. Then, an adaptive locomotion on different ground properties is proposed. The dynamic alternating tripod trotting gait is developed to control the robot, and the parameters of active compliance control change with the terrain. Finally, the method is integrated on a hexapod robot and tested by real experiments. Our method is shown effective for the hexapod robot to walk on concrete, wood, grass, and foam. The strategies and experimental results can be a valuable reference for other legged robots applied in outdoor environments.

Cuckoo Search Based Decision Fusion Techniques for Natural Terrain Understanding

2014 ◽  
Vol 5 (2) ◽  
pp. 1-21 ◽  
Author(s):  
Arpita Sharma ◽  
Samiksha Goel
Keyword(s):  
Remote Sensing ◽  
Satellite Images ◽  
Remote Sensing Data ◽  
Cuckoo Search ◽  
Decision Fusion ◽  
Majority Voting ◽  
Natural Terrain ◽  
Terrain Features ◽  
Level Fusion ◽  
Better Than

This paper proposes two novel nature inspired decision level fusion techniques, Cuckoo Search Decision Fusion (CSDF) and Improved Cuckoo Search Decision Fusion (ICSDF) for enhanced and refined extraction of terrain features from remote sensing data. The developed techniques derive their basis from a recently introduced bio-inspired meta-heuristic Cuckoo Search and modify it suitably to be used as a fusion technique. The algorithms are validated on remote sensing satellite images acquired by multispectral sensors namely LISS3 Sensor image of Alwar region in Rajasthan, India and LANDSAT Sensor image of Delhi region, India. Overall accuracies obtained are substantially better than those of the four individual terrain classifiers used for fusion. Results are also compared with majority voting and average weighing policy fusion strategies. A notable achievement of the proposed fusion techniques is that the two difficult to identify terrains namely barren and urban are identified with similar high accuracies as other well identified land cover types, which was not possible by single analyzers.

Sign in / Sign up

Export Citation Format

Share Document