Soft Foot Sensor Design and Terrain Classification for Dynamic Legged Locomotion

Guo, Xiaojun; Blaise, Bryan; Molnar, Jennifer L.; Coholich, Jeremiah; Padte, Shantanu; Zhao, Ye; Hammond, Frank L.

doi:10.1109/robosoft48309.2020.9115990

Cited by 10 publications

(4 citation statements)

References 23 publications

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“…However, the majority only used either slopes, steps or random bricks [3, 4, 76-81, 83-89, 91, 93-102, 104, 107]. Only six more terrains where found: stairs [80,89,92], rocky terrain replica [105], ditch [89], soft terrain [103,106] and grassland [93,107]. The most complete approach considering several terrains was the DARPA challenge [93], in which humanoid robots were challenged to go through level, rough and sloped terrains, loose soil, rocks, and natural-like obstacles such as bushes, trees and ditches.…”

Section: Methodological Aspectsmentioning

confidence: 99%

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Legged locomotion over irregular terrains: state of the art of human and robot performance

et al. 2022

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Legged robotic technologies have moved out of the lab to operate in real environments, characterized by a wide variety of unpredictable irregularities and disturbances, all this in close proximity with humans. Demonstrating the ability of current robots to move robustly and reliably in these conditions is becoming essential to prove their safe operation. Here, we report an in-depth literature review aimed at verifying the existence of common or agreed protocols and metrics to test the performance of legged system in realistic environments. We primarily focused on three types of robotic technologies, i.e., hexapods, quadrupeds and bipeds. We also included a comprehensive overview on human locomotion studies, being it often considered the gold standard for performance, and one of the most important sources of bioinspiration for legged machines. We discovered that very few papers have rigorously studied robotic locomotion under irregular terrain conditions. On the contrary, numerous studies have addressed this problem on human gait, being nonetheless of highly heterogeneous nature in terms of experimental design. This lack of agreed methodology makes it challenging for the community to properly assess, compare and predict the performance of existing legged systems in real environments. On the one hand, this work provides a library of methods, metrics and experimental protocols, with a critical analysis on the limitations of the current approaches and future promising directions. On the other hand, it demonstrates the existence of an important lack of benchmarks in the literature, and the possibility of bridging different disciplines, e.g., the human and robotic, towards the definition of standardized procedures that will boost not only the scientific development of better bioinspired solutions, but also their market uptake.

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Section: Methodological Aspectsmentioning

confidence: 99%

“…For this matter, they proposed a stability margin to choose between different step sequences. Other authors [105,106] focused on identifying and classifying ground materials and surface transitions using sensors located at the robot's feet to automatically adjust biped controllers to the specific terrain conditions.…”

Section: Scientific Evidencementioning

confidence: 99%

Legged locomotion over irregular terrains: state of the art of human and robot performance

et al. 2022

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“…Terrain sensors provide valuable data, enabling adaptive movement strategies to ensure stability and efficiency across various terrains [74], [149], [158]. Table 6 compiles these advancements, highlighting the diverse sensors used for terrain recognition and control in bipedal robots, including bio-inspired feet and neural network terrain classification [149], [151], [154], [155].…”

Section: Controller Unit Sensory and Perception Systems In Bipedal Wh...mentioning

confidence: 99%

Evolution, Design, and Future Trajectories on Bipedal Wheel-legged Robot: A Comprehensive Review

Mansor,

Irawan,

Abas

2023

IJRCS

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This comprehensive review delves into the realm of bipedal wheel-legged robots, focusing on their design, control, and applications in assistive technology and disaster mitigation. Drawing insights from various fields such as robotics, computer science, and biomechanics, it offers a holistic understanding of these robots' stability, adaptability, and efficiency. The analysis encompasses optimization techniques, sensor integration, machine learning, and adaptive control methods, evaluating their impact on robot capabilities. Emphasizing the need for adaptable, terrain-aware control algorithms, the review explores the untapped potential of machine learning and soft robotics in enhancing performance across diverse operational scenarios. It highlights the advantages of hybrid models combining legged and wheeled mobility while stressing the importance of refining control frameworks, trajectory planning, and human-robot interactions. The concept of integrating soft and compliant mechanisms for improved adaptability and resilience is introduced. Identifying gaps in current research, the review suggests future directions for investigation in the fields of robotics and control engineering, addressing the evolution and terrain adaptability of bipedal wheel-legged robots, control, stability, and locomotion, as well as integrated sensory and perception systems, microcontrollers, cutting-edge technology, and future design and control directions.

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“…There are many tactile perception works based on different sensor information, such as force and moment [ 27 ], vibration [ 28 ], execution errors [ 29 ], etc. It is worth mentioning that the fusion of multiple sensors can achieve higher accuracy, and much work has shown its advantages [ 30 , 31 ]. Although the haptic approach provides the most reliable data on the physical features of the terrain, it becomes powerless when performing remote planning.…”

Section: Introductionmentioning

confidence: 99%

Learning physical characteristics like animals for legged robots

Ding

et al. 2023

National Science Review

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Physical characteristics of terrains, such as softness and friction, provide essential information for legged robots to avoid non-geometric obstacles, like mires and slippery stones, in the wild. The perception of such characteristics often relies on tactile perception and vision prediction. Although tactile perception is more accurate, it is limited to close-range use; by contrast, establishing a supervised or self-supervised contactless prediction system using computer vision requires adequate labeled data and lacks the ability to adapt to the dynamic environment. In this paper, we simulate the behavior of animals and propose an unsupervised learning framework for legged robots to learn the physical characteristics of terrains, which is the first report to manage it online, incrementally, and with the ability to solve cognitive conflicts. The proposed scheme allows robots to interact with the environment and adjust their cognition in real time, therefore endowing robots with the adaptation ability. Indoor and outdoor experiments on a hexapod robot are carried out to show that the robot can extract tactile and visual features of terrains to create cognitive networks independently; an associative layer between visual and tactile features is created during the robot’s exploration; with the layer, the robot can autonomously generate a physical segmentation model of terrains and solve cognitive conflicts in an ever-changing environment, facilitating its safe navigation.

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Soft Foot Sensor Design and Terrain Classification for Dynamic Legged Locomotion

Cited by 10 publications

References 23 publications

Legged locomotion over irregular terrains: state of the art of human and robot performance

Legged locomotion over irregular terrains: state of the art of human and robot performance

Evolution, Design, and Future Trajectories on Bipedal Wheel-legged Robot: A Comprehensive Review

Learning physical characteristics like animals for legged robots

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