A hybrid tactile sensor-based obstacle overcoming method for hexapod walking robots
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ORIGINAL RESEARCH PAPER
A hybrid tactile sensor-based obstacle overcoming method for hexapod walking robots Mindaugas Luneckas1 · Tomas Luneckas1 · Dainius Udris1 · Darius Plonis2 Robertas Damaševiˇcius4
3· · Rytis Maskeliunas ¯
Received: 23 May 2020 / Accepted: 19 October 2020 © The Author(s) 2020
Abstract Walking robots are considered as a promising solution for locomotion across irregular or rough terrain. While wheeled or tracked robots require flat surface like roads or driveways, walking robots can adapt to almost any terrain type. However, overcoming diverse terrain obstacles still remains a challenging task even for multi-legged robots with a high number of degrees of freedom. Here, we present a novel method for obstacle overcoming for walking robots based on the use of tactile sensors and generative recurrent neural network for positional error prediction. By using tactile sensors positioned on the front side of the legs, we demonstrate that a robot is able to successfully overcome obstacles close to robots height in the terrains of different complexity. The proposed method can be used by any type of a legged machine and can be considered as a step toward more advanced walking robot locomotion in unstructured terrain and uncertain environment. Keywords Hexapod robot · Obstacle overcoming · Tactile sensors · Bio-inspired robotics · Recurrent neural network
1 Introduction Most of earth’s terrain is uneven and full of different kinds of obstacles, which makes it difficult for traditional wheeled vehicles to reach their destination in natural environment if roads are not available [1]. Such vehicles are especially demanded for a variety of critical applications such as rescue [2], disaster management [3] or border security patrol [4]. For off-road environment, new types of vehicles are being developed. The researchers aim to design autonomously navigating robots that can acquire and benefit from the data collected from their environment in order to overcome any obstacles and perform steady navigation in uncertain environment [5–7]. While image recognition of data received,
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Robertas Damaševiˇcius [email protected]
1
Department of Electrical Engineering, Vilnius Gediminas Technical University, Vilnius, Lithuania
2
Department of Electronic Systems, Vilnius Gediminas Technical University, Vilnius, Lithuania
3
Department of Applied Informatics, Vytautas Magnus University, Kaunas, Lithuania
4
Faculty of Applied Mathematics, Silesian University of Technology, Gliwice, Poland
for example, from Kinect RGB-D cameras, can be used for localization and mapping in unknown environments [8], it still does not solve the problem of overcoming the obstacles. Often, the nature provides inspiration of the development of such vehicles [9], motivating the design of new and more universal vehicles such as robots. The most prevalent locomotion type in nature is walking. No wheeled or tracked locomotion can be found between the kingdoms of animals, insects, birds or fish. Thus, biped, quadruped or hexapod
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