Improving Climbing Performance Using Passive Tail in Lizard-Inspired Robot

Abstract Lizards are excellent climbers and effectively utilize their tail to actively counter the destabilizing pitching moment during climbing. Taking inspiration from the use of a tail for imparting stability we designed a compliant passive tail to improve the climbing performance of a wall climbing lizard-inspired robot developed in the past by our research group [1, 2]. This paper presents the incorporation of the spring-actuated tail into climbing robots to improve their stability and climbing capabilities. A spring-actuated tail helps in regaining the stability during momentary adhesive failure making the robot more reliable. However, there is no external support for the tail to avoid slipping during momentary adhesive failure. To improve the climbing performance and reduce the chances of failure, A flexible pressure-sensitive adhesive tip has been incorporated on the compliant passive tail to enhance the climbing stability. The climbing capabilities of the proposed design are compared with two different conditions: a robot with and without a tail under two different terrains: hard (Acrylic sheet) and soft (Fitness mat). The experimental results demonstrate that the robot equipped with a tail featuring a flexible adhesive tip achieves the best climbing performance on hard terrains with a maximum slope of 65°, while a tail lacking a flexible adhesive tip achieves superior climbing performance on soft terrains with a maximum slope of 40°. This approach enables a climbing robot to navigate and ascend various terrains, thereby expanding its operational capabilities to encompass areas with different terrains. This versatility is especially valuable in tasks such as inspection, exploration, and construction.

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Publication Details

Published
2024-08-25
DOI
https://doi.org/10.1115/detc2024-143646
Primary Topic
Modular Robots and Swarm Intelligence
Type
article
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article

Improving Climbing Performance Using Passive Tail in Lizard-Inspired Robot

Atul Thakur, Kadali Mani Sankar, Kodidasu Pranav
Modular Robots and Swarm Intelligence
article

Improving Climbing Performance Using Passive Tail in Lizard-Inspired Robot

Atul Thakur, Kadali Mani Sankar, Kodidasu Pranav
article en

Abstract

Abstract Lizards are excellent climbers and effectively utilize their tail to actively counter the destabilizing pitching moment during climbing. Taking inspiration from the use of a tail for imparting stability we designed a compliant passive tail to improve the climbing performance of a wall climbing lizard-inspired robot developed in the past by our research group [1, 2]. This paper presents the incorporation of the spring-actuated tail into climbing robots to improve their stability and climbing capabilities. A spring-actuated tail helps in regaining the stability during momentary adhesive failure making the robot more reliable. However, there is no external support for the tail to avoid slipping during momentary adhesive failure. To improve the climbing performance and reduce the chances of failure, A flexible pressure-sensitive adhesive tip has been incorporated on the compliant passive tail to enhance the climbing stability. The climbing capabilities of the proposed design are compared with two different conditions: a robot with and without a tail under two different terrains: hard (Acrylic sheet) and soft (Fitness mat). The experimental results demonstrate that the robot equipped with a tail featuring a flexible adhesive tip achieves the best climbing performance on hard terrains with a maximum slope of 65°, while a tail lacking a flexible adhesive tip achieves superior climbing performance on soft terrains with a maximum slope of 40°. This approach enables a climbing robot to navigate and ascend various terrains, thereby expanding its operational capabilities to encompass areas with different terrains. This versatility is especially valuable in tasks such as inspection, exploration, and construction.

Indian Institute of Technology Patna (IN)
Openalex Percentile: Top 80%
Modular Robots and Swarm Intelligence
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