Terrain Classification from Body-mounted Cameras during Human Locomotion

Abstract—This paper presents a novel algorithm for terrain type classification based on monocular video captured from the viewpoint of human locomotion. A texture-based algorithm is developed to classify the path ahead into multiple groups that can be used to support terrain classification. Gait is taken into account in two ways. Firstly, for key frame selection, when regions with homogeneous texture characteristics are updated, the fre-quency variations of the textured surface are analysed and used to adaptively define filter coefficients. Secondly, it is incorporated in the parameter estimation process where probabilities of path consistency are employed to improve terrain-type estimation. When tested with multiple classes that directly affect mobility a hard surface, a soft surface and an unwalkable area- our proposed method outperforms existing methods by up to 16%, and also provides improved robustness. Index Terms—texture, classification, recursive filter, terrain classification I

Locomotion system for ground mobile robots in uneven and unstructured environments

One of the technology domains with the greatest growth rates nowadays is service robots. The extensive use of ground mobile robots in environments that are unstructured or structured for humans is a promising challenge for the coming years, even though Automated Guided Vehicles (AGV) moving on flat and compact grounds are already commercially available and widely utilized to move components and products inside indoor industrial buildings. Agriculture, planetary exploration, military operations, demining, intervention in case of terrorist attacks, surveillance, and reconnaissance in hazardous conditions are important application domains. Due to the fact that it integrates the disciplines of locomotion, vision, cognition, and navigation, the design of a ground mobile robot is extremely interdisciplinary. In terms of mechanics, ground mobile robots, with the exception of those designed for particular surroundings and surfaces (such as slithering or sticky robots), can move on wheels (W), legs (L), tracks (T), or hybrids of these concepts (LW, LT, WT, LWT). In terms of maximum speed, obstacle crossing ability, step/stair climbing ability, slope climbing ability, walking capability on soft terrain, walking capability on uneven terrain, energy efficiency, mechanical complexity, control complexity, and technology readiness, a systematic comparison of these locomotion systems is provided in [1]. Based on the above-mentioned classification, in this thesis, we first introduce a small-scale hybrid locomotion robot for surveillance and inspection, WheTLHLoc, with two tracks, two revolving legs, two active wheels, and two passive omni wheels. The robot can move in several different ways, including using wheels on the flat, compact ground,[1] tracks on soft, yielding terrain, and a combination of tracks, legs, and wheels to navigate obstacles. In particular, static stability and non-slipping characteristics are considered while analyzing the process of climbing steps and stairs. The experimental test on the first prototype has proven the planned climbing maneuver’s efficacy and the WheTLHLoc robot's operational flexibility. Later we present another development of WheTLHLoc and introduce WheTLHLoc 2.0 with newly designed legs, enabling the robot to deal with bigger obstacles. Subsequently, a single-track bio-inspired ground mobile robot's conceptual and embodiment designs are presented. This robot is called SnakeTrack. It is designed for surveillance and inspection activities in unstructured environments with constrained areas. The vertebral column has two end modules and a variable number of vertebrae linked by compliant joints, and the surrounding track is its essential component. Four motors drive the robot: two control the track motion and two regulate the lateral flexion of the vertebral column for steering. The compliant joints enable limited passive torsion and retroflection of the vertebral column, which the robot can use to adapt to uneven terrain and increase traction. Eventually, the new version of SnakeTrack, called 'Porcospino', is introduced with the aim of allowing the robot to move in a wider variety of terrains. The novelty of this thesis lies in the development and presentation of three novel designs of small-scale mobile robots for surveillance and inspection in unstructured environments, and they employ hybrid locomotion systems that allow them to traverse a variety of terrains, including soft, yielding terrain and high obstacles. This thesis contributes to the field of mobile robotics by introducing new design concepts for hybrid locomotion systems that enable robots to navigate challenging environments. The robots presented in this thesis employ modular designs that allow their lengths to be adapted to suit specific tasks, and they are capable of restoring their correct position after falling over, making them highly adaptable and versatile. Furthermore, this thesis presents a detailed analysis of the robots' capabilities, including their step-climbing and motion planning abilities. In this thesis we also discuss possible refinements for the robots' designs to improve their performance and reliability. Overall, this thesis's contributions lie in the design and development of innovative mobile robots that address the challenges of surveillance and inspection in unstructured environments, and the analysis and evaluation of these robots' capabilities. The research presented in this thesis provides a foundation for further work in this field, and it may be of interest to researchers and practitioners in the areas of robotics, automation, and inspection. As a general note, the first robot, WheTLHLoc, is a hybrid locomotion robot capable of combining tracked locomotion on soft terrains, wheeled locomotion on flat and compact grounds, and high obstacle crossing capability. The second robot, SnakeTrack, is a small-size mono-track robot with a modular structure composed of a vertebral column and a single peripherical track revolving around it. The third robot, Porcospino, is an evolution of SnakeTrack and includes flexible spines on the track modules for improved traction on uneven but firm terrains, and refinements of the shape of the track guidance system. This thesis provides detailed descriptions of the design and prototyping of these robots and presents analytical and experimental results to verify their capabilities

Adaptive Locomotion: The Cylindabot Robot

Adaptive locomotion is an emerging field of robotics due to the complex interaction between the robot and its environment. Hybrid locomotion is where a robot has more than one mode of locomotion and potentially delivers the benefits of both, however, these advantages are often not quantified or applied to new scenarios. The classic approach is to design robots with a high number of degrees of freedom and a complex control system, whereas an intelligent morphology can simplify the problem and maintain capabilities. Cylindabot is designed to be a minimally actuated hybrid robot with strong terrain crossing capabilities. By limiting the number of motors, this reduces the robot's weight and means less reinforcement is needed for the physical frame or drive system. Cylindabot uses different drive directions to transform between using wheels or legs. Cylindabot is able to climb a slope of 32 degrees and a step ratio of 1.43 while only being driven by two motors. A physical prototype and simulation models show that adaptation is optimal for a range of terrain (slopes, steps, ridges and gaps). Cylindabot successfully adapts to a map environment where there are several routes to the target location. These results show that a hybrid robot can increase its terrain capabilities when changing how it moves and that this adaptation can be applied to wider environments. This is an important step to have hybrid robots being deployed to real situations

Integration of aerial and terrestrial locomotion modes in a bioinspired robotic system

In robotics, locomotion is a fundamental task for the development of high-level activities such as navigation. For a robotic system, the challenge of evading environmental obstacles depends both on its physical capabilities and on the strategies followed to achieve it. Thus, a robot with the ability to develop several modes of locomotion (walking, flying or swimming) has a greater probability of success in achieving its goal than a robot that develops only one. In nature, Hymenoptera insects use terrestrial and aerial modes of locomotion to carry out their activities. Mimicry the physical capabilities of these insects opens the possibility of improvements in the area of robotic locomotion. Therefore, this work seeks to generate a bio-inspired robotic system that integrates the terrestrial and aerial modes of locomotion. The methodology used in this research project has considered the anatomical study and characterization of Hymenoptera insects locomotion, the proposal of conceptual models that integrate terrestrial and aerial modes locomotion, the construction of a physical platform and experimental testing of the system. In addition, a gait generation approach based on an artificial nervous system of coupled nonlinear oscillators has been proposed. This approach has resulted in the generation of a coherent and functional gait pattern that, in combination with the flight capabilities of the system, has constituted an aero-terrestrial robot. The results obtained in this work include the construction of a bioinspired physical platform, the generation of the gait process using an artificial nervous system and the experimental tests on the integration of aero-terrestrial locomotion.Conacyt - Becario Naciona

A Hierarchical Strategy for Learning of Robot Walking Strategies in Natural Terrain Environments

©2007 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Presented at the 2007 IEEE International Conference on Systems, Man and Cybernetics, October 7-10, 2007, Montréal.DOI: 10.1109/ICSMC.2007.4413682In this paper, we present a hierarchical methodology that learns new walking gaits autonomously while operating in an uncharted environment, such as on the Mars planetary surface or in the remote Antarctica environment. The focus is to maintain persistent forward locomotion along the body axis, while navigating in natural terrain environments. The hierarchical strategy consists of a finite state machine that models the state of leg orientations coupled with a modified evolutionary algorithm to learn necessary leg movement sequences. Locomotion behavior is assessed by monitoring the robot's progress toward a specified goal location. Details of the methodology are discussed, and experimental results with a six-legged robot are presented

The OmniTread OT-4 serpentine robot—design and performance

Serpentine robots are slender, multi-segmented vehicles designed to provide greater mobility than conventional mobile robots. Serpentine robots are ideally suited for urban search and rescue, military intelligence gathering, and inspection tasks in hazardous or inaccessible environments. One such serpentine robot, developed at the University of Michigan, is the “OmniTread OT-4.” The OT-4 comprises seven segments, which are linked to each other by six joints. The OT-4 can climb over obstacles that are much higher than the robot itself, propel itself inside pipes of different diameters, and traverse difficult terrain, such as rocks or the rubble of a collapsed structure. The foremost and unique design characteristic of the OT-4 is the use of pneumatic bellows to actuate the joints. The pneumatic bellows allow the simultaneous control of position and stiffness for each joint. Controllable stiffness is important in serpentine robots, which require stiff joints to cross gaps and compliant joints to conform to rough terrain for effective propulsion. Another unique feature of the OmniTread design is the coverage of all four sides of each segment with drive tracks. This design makes the robot indifferent to rollovers, which are bound to happen when the slender bodies of serpentine robots travel over rugged terrain. This paper describes the OmniTread concept and some of its technical features in some detail. In the Experiment Results Section, photographs of successful obstacle traverses illustrate the abilities of the OT-4. © 2007 Wiley Periodicals, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/56171/1/20196_ftp.pd

Uncertainty Characterisation of Mobile Robot Localisation Techniques using Optical Surveying Grade Instruments

Recent developments in localisation systems for autonomous robotic technology have been a driving factor in the deployment of robots in a wide variety of environments. Estimating sensor measurement noise is an essential factor when producing uncertainty models for state-of-the-art robotic positioning systems. In this paper, a surveying grade optical instrument in the form of a Trimble S7 Robotic Total Station is utilised to dynamically characterise the error of positioning sensors of a ground based unmanned robot. The error characteristics are used as inputs into the construction of a Localisation Extended Kalman Filter which fuses Pozyx Ultra-wideband range measurements with odometry to obtain an optimal position estimation, all whilst using the path generated from the remote tracking feature of the Robotic Total Station as a ground truth metric. Experiments show that the proposed method yields an improved positional estimation compared to the Pozyx systems’ native firmware algorithm as well as producing a smoother trajectory