KAIRO 3: Moving over stairs &amp;amp; unknown obstacles with reconfigurable snake-like robots

Pfotzer, L.; Staehler, M.; Hermann, A. M.; Roennau, Arne; Dillmann, Rüdiger

doi:10.1109/ecmr.2015.7324209

Cited by 23 publications

(13 citation statements)

References 22 publications

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“…It emphasizes two important challenges of SLAM in this type of robot in comparison with existing approaches of SLAM: on one hand, the use of odometry-less models, and on the other hand, the lack of features or landmarks that characterizes navigation environments such as the inside of tunnels and pipes, which is a typical focus for snake robots. A rotating LiDAR is used in [65] to scan the environment and generate a 2.5 dimensional map that then can be used to perform motion planning in 3D. The main objective of this system is to overcome challenging obstacles such as stairs, for which the robot also relies on active wheels.…”

Section: Survey Of Environment Perception For Locomotion In Snake Robotsmentioning

confidence: 99%

Perception-Driven Obstacle-Aided Locomotion for Snake Robots: The State of the Art, Challenges and Possibilities †

et al. 2017

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In nature, snakes can gracefully traverse a wide range of different and complex environments. Snake robots that can mimic this behaviour could be fitted with sensors and transport tools to hazardous or confined areas that other robots and humans are unable to access. In order to carry out such tasks, snake robots must have a high degree of awareness of their surroundings (i.e., perception-driven locomotion) and be capable of efficient obstacle exploitation (i.e., obstacle-aided locomotion) to gain propulsion. These aspects are pivotal in order to realise the large variety of possible snake robot applications in real-life operations such as fire-fighting, industrial inspection, search-and-rescue, and more. In this paper, we survey and discuss the state of the art, challenges, and possibilities of perception-driven obstacle-aided locomotion for snake robots. To this end, different levels of autonomy are identified for snake robots and categorised into environmental complexity, mission complexity, and external system independence. From this perspective, we present a step-wise approach on how to increment snake robot abilities within guidance, navigation, and control in order to target the different levels of autonomy. Pertinent to snake robots, we focus on current strategies for snake robot locomotion in the presence of obstacles. Moreover, we put obstacle-aided locomotion into the context of perception and mapping. Finally, we present an overview of relevant key technologies and methods within environment perception, mapping, and representation that constitute important aspects of perception-driven obstacle-aided locomotion.

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Section: Survey Of Environment Perception For Locomotion In Snake Robotsmentioning

confidence: 99%

Perception-Driven Obstacle-Aided Locomotion for Snake Robots: The State of the Art, Challenges and Possibilities †

et al. 2017

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“…An interesting approach, called obstacle aided locomotion, has been used in reference [29,30] wherein the obstacles are used to generate reaction forces for locomotion, thus mimicking natural snakes, and in a sense obviating the problem of obstacle avoidance. Some of the recent papers also deal with the problem using Rapidly Exploring Random Tree (RRT) algorithm [31] and hybrid of RRT and Motion Primitives(MP) algorithm [32]. However, these algorithms are partly stochastic in nature and cannot guarantee asymptotic optimality.…”

Section: Comparison With Existing Algorithmsmentioning

confidence: 99%

Trajectory Planning and Obstacle Avoidance for Hyper-Redundant Serial Robots

Menon

Ravi

Ghosal

2017

Journal of Mechanisms and Robotics

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Hyper-redundant snakelike serial robots are of great interest due to their application in search and rescue during disaster relief in highly cluttered environments and recently in the field of medical robotics. A key feature of these robots is the presence of a large number of redundant actuated joints and the associated well-known challenge of motion planning. This problem is even more acute in the presence of obstacles. Obstacle avoidance for point bodies, nonredundant serial robots with a few links and joints, and wheeled mobile robots has been extensively studied, and several mature implementations are available. However, obstacle avoidance for hyper-redundant snakelike robots and other extended articulated bodies is less studied and is still evolving. This paper presents a novel optimization algorithm, derived using calculus of variation, for the motion planning of a hyper-redundant robot where the motion of one end (head) is an arbitrary desired path. The algorithm computes the motion of all the joints in the hyper-redundant robot in a way such that all its links avoid all obstacles present in the environment. The algorithm is purely geometric in nature, and it is shown that the motion in free space and in the vicinity of obstacles appears to be more natural. The paper presents the general theoretical development and numerical simulations results. It also presents validating results from experiments with a 12-degree-of-freedom (DOF) planar hyper-redundant robot moving in a known obstacle field.

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“…For instance, revised GA with customized fitness functions are implemented to solve the path planning problem of the lattice modules in M-Lattice robot [22]. To plan the path to overcome stairs or obstacles, KAIRO 3 robot makes use of extended RRT* algorithm [23] to autonomously calculate the actions required for the tasks [24]. Research has also been conducted to provide heuristic-based algorithms [25] and distributed planning algorithms [26] for lattice-type inter-reconfigurable robots that are less architecture-specific.…”

Section: Introductionmentioning

confidence: 99%

Optimization Complete Area Coverage by Reconfigurable hTrihex Tiling Robot

Parween

Mohan

et al. 2020

Sensors

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Completed area coverage planning (CACP) plays an essential role in various fields of robotics, such as area exploration, search, rescue, security, cleaning, and maintenance. Tiling robots with the ability to change their shape is a feasible solution to enhance the ability to cover predefined map areas with flexible sizes and to access the narrow space constraints. By dividing the map into sub-areas with the same size as the changeable robot shapes, the robot can plan the optimal movement to predetermined locations, transform its morphologies to cover the specific area, and ensure that the map is completely covered. The optimal navigation planning problem, including the least changing shape, shortest travel distance, and the lowest travel time while ensuring complete coverage of the map area, are solved in this paper. To this end, we propose the CACP framework for a tiling robot called hTrihex with three honeycomb shape modules. The robot can shift its shape into three different morphologies ensuring coverage of the map with a predetermined size. However, the ability to change shape also raises the complexity issues of the moving mechanisms. Therefore, the process of optimizing trajectories of the complete coverage is modeled according to the Traveling Salesman Problem (TSP) problem and solved by evolutionary approaches Genetic Algorithm (GA) and Ant Colony Optimization (ACO). Hence, the costweight to clear a pair of waypoints in the TSP is defined as the required energy shift the robot between the two locations. This energy corresponds to the three operating processes of the hTrihex robot: transformation, translation, and orientation correction. The CACP framework is verified both in the simulation environment and in the real environment. From the experimental results, proposed CACP capable of generating the Pareto-optimal outcome that navigates the robot from the goal to destination in various workspaces, and the algorithm could be adopted to other tiling robot platforms with multiple configurations.

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KAIRO 3: Moving over stairs & unknown obstacles with reconfigurable snake-like robots

Cited by 23 publications

References 22 publications

Perception-Driven Obstacle-Aided Locomotion for Snake Robots: The State of the Art, Challenges and Possibilities †

Perception-Driven Obstacle-Aided Locomotion for Snake Robots: The State of the Art, Challenges and Possibilities †

Trajectory Planning and Obstacle Avoidance for Hyper-Redundant Serial Robots

Optimization Complete Area Coverage by Reconfigurable hTrihex Tiling Robot

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