Uneven Environments Research Articles

Simultaneous Search and Tracking of Non-cooperative Mobile Targets Using Multiple UAVs in Uneven Environments

Simultaneous Search and Tracking of Non-cooperative Mobile Targets Using Multiple UAVs in Uneven Environments

DEVELOPING A MOTION MECHANISM FOR A SINGLE MODULE IN A SELF-RECONFIGURABLE MODULAR MICROROBOTICS SYSTEM BY USING EXTERNAL MAGNETIC ACTUATORS

In microrobotics field, self-reconfigurable modular robots (SRMRs) offer several advantages including adaptation to uneven environments, the capability of handling various sets of tasks, and continuous operation in the case of a malfunction of a single module. The current research direction in self-reconfigurable robotic systems is towards reaching million level number of modules working in coherence by means of locomotion, self-reconfiguration, and information flow. This research direction comes with new challenges such as miniaturizing the modules. One should consider looking for alternative ways of locomotion and self-reconfiguration when dealing with SRMRs having million level number of modules. Externally actuating the modules can be a good alternative to micro SRMRs. In this study, we developed a novel motion mechanism for a single module in a micro SRMR system by using external magnetic actuators. An assembly of elastic microtubes and permanent magnets is attached inside a cube-shaped module and periodic motion of the assembly is applied. The motion of a single microtube with permanent magnets inside is generated by using COMSOL Multiphysics software. The results of the simulations are compared with theoretical values to validate the motion mechanism that is introduced in the study.

Trajectory Generation and Optimization Using the Mutual Learning and Adaptive Ant Colony Algorithm in Uneven Environments

Aiming at the trajectory generation and optimization of mobile robots in complex and uneven environments, a hybrid scheme using mutual learning and adaptive ant colony optimization (MuL-ACO) is proposed in this paper. In order to describe the uneven environment with various obstacles, a 2D-H map is introduced in this paper. Then an adaptive ant colony algorithm based on simulated annealing (SA) is proposed to generate initial trajectories of mobile robots, where based on a de-temperature function of the simulated annealing algorithm, the pheromone volatilization factor is adaptively adjusted to accelerate the convergence of the algorithm. Moreover, the length factor, height factor, and smooth factor are considered in the comprehensive heuristic function of ACO to adapt to uneven environments. Finally, a mutual learning algorithm is designed to further smooth and shorten initial trajectories, in which different trajectory node sequences learn from each other to acquire the shortest trajectory sequence to optimize the trajectory. In order to verify the effectiveness of the proposed scheme, MuL-ACO is compared with several well-known and novel algorithms in terms of running time, trajectory length, height, and smoothness. The experimental results show that MuL-ACO can generate a collision-free trajectory with a high comprehensive quality in uneven environments.

Dynamic path planning over CG-Space of 10DOF Rover with static and randomly moving obstacles using RRT* rewiring

AbstractDynamic path planning is a core research content for intelligent robots. This paper presents a CG-Space-based dynamic path planning and obstacle avoidance algorithm for 10 DOF wheeled mobile robot (Rover) traversing over 3D uneven terrains. CG-Space is the locus of the center of gravity location of Rover while moving on a 3D terrain. A CG-Space-based modified RRT* samples a random space tree structure. Dynamic rewiring this tree can handle the randomly moving obstacles and target in real time. Simulations demonstrate that the Rover can obtain the target location in 3D uneven dynamic environments with fixed and randomly moving obstacles.

위험지역을 고려하는 수정된 JPS (jump point search) 기법 개발

Graph search-based path planning algorithms have been widely applied for path planning in autonomous robot systems. Among these algorithms, the jump point search (JPS) method, adopted in this study, is a variant of the well-known algorithm A* and utilizes a unique node search strategy called “jump.” The jump makes the JPS method one of the fastest graph search-based path planning algorithms. However, while the A* algorithm can be easily modified for identifying uneven environmental conditions (e.g., danger zones), danger zones cannot be handled in the JPS algorithm because the jump strategy removes plenty of nodes, including the essential ones for avoiding danger zones. To obtain a reasonable path in uneven environments, this study proposes a modified version of the JPS algorithm called the modified jump search method (MJPS). The MJPS method enables danger zones to be recognized and thus avoided during path generation by introducing bordering and additional nodes. To validate the proposed method, numerical simulations will be performed, and the results will be analyzed by comparing it with the A*-based path planning results.

Volunteer Urban Environmental Stewardship, Emotional Economies of Care, and Productive Power in Philadelphia

Recent efforts to increase urban forests and greenspaces rely on the volunteer labor of individuals and environmental nonprofits. The estimation of market values has often justified urban greening. These neoliberal approaches to urban environmental governance have been heavily critiqued, revealing the uneven power relationships and urban environments that result. This paper aims to move beyond such critiques by exploring how the reproduction of urban nature can be valued outside of the market. Fieldwork with volunteers participating in environmental stewardship in Philadelphia revealed their participation was motivated by intense emotional attachments to their neighborhoods, other participants, and nonhuman others, leading me to propose emotional economies of care as an alternative framework. The circulation of emotions and affects between participants, places, and nonhuman others forms an emotional economy. The generative power of this circulation makes emotional economies of care collective bodies or multiplicities. Furthermore, these multiplicities produce power from below, in counterpoint to the top down power of neoliberal environmentalities. However, just as these multiplicities come together, they can come apart or change directions. I close with ideas on how emotional ecologies and economies of care can be brought into being and processes of change within them shepherded in progressive ways.

Kinematic Design Analysis and Optimization of Mobility System Using MATLAB

In this research work, several sophisticated types of equipment and automation have been studied, points taken and considered to realise the locomotion of modern territory of all uneven environments. One of the most main mission and structure of this study is the preferred simplicity of the bipedal walking locomotion system. The study included from simple to complicated legs as like single-legged, like humanoid and up to sixteen legs like a caterpillar. Most of the bipedal walking robots are with research study and we concentrated to emphasizes the significance of robotic legged motion stability in the compact. These bipedal walking robots can walk on rough surfaces, turn efficiently and climb staircase if needed. In particular, a suitable bipedal walking model having an upper link and a lower link will make the system to the desired motions, which has been experimentally exposed to provide a stable walking system. The MATLAB software tool is used to optimize the mechanical constraints and to compare, analyse and investigate the influence of motion stability. The simulation results show a possible performance of projected leg bipedal walking mechanism.

Stepping pattern changes in the caterpillar Manduca sexta: the effects of orientation and substrate.

Most animals can successfully travel across cluttered, uneven environments and cope with enormous changes in surface friction, deformability and stability. However, the mechanisms used to achieve such remarkable adaptability and robustness are not fully understood. Even more limited is the understanding of how soft, deformable animals such as tobacco hornworm Manduca sexta (caterpillars) can control their movements as they navigate surfaces that have varying stiffness and are oriented at different angles. To fill this gap, we analyzed the stepping patterns of caterpillars crawling on two different types of substrate (stiff and soft) and in three different orientations (horizontal and upward/downward vertical). Our results show that caterpillars adopt different stepping patterns (i.e. different sequences of transition between the swing and stance phases of prolegs in different body segments) based on substrate stiffness and orientation. These changes in stepping pattern occur more frequently in the upward vertical orientation. The results of this study suggest that caterpillars can detect differences in the material properties of the substrate on which they crawl and adjust their behavior to match those properties.

Auditory cues assist patients with Parkinson’s disease (on and off L-dopa) during obstacle crossing

People with Parkinson’s disease (PD) have an impaired locomotor pattern. As a result, the capacity of walking independently and the interaction with the environment can be impairment. Uneven environments can challenge even more the motor control of these patients to perform the locomotor tasks successfully. Besides of the levodopa therapy, the auditory cues have also been utilized to improve the gait parameters. However, the effects of auditory cues in gait during obstacle avoidance and the association with the levodopa effects are not known. The aim of this study was to investigate the effects of AC during obstacle crossing in people with PD (on and off L-dopa) and in healthy control participants.A total of 30 individuals participated in the study, including 15 PD patients who were tested both on and off L-dopa and 15 healthy adult controls. The task consisted of stepping over an obstacle located in the middle of the path under two conditions, i.e., cued and non-cued. We used kinematic, kinetic and electromyographic analyses to evaluate individuals' locomotor patterns. Groups differed signifi cantly from each other for all analyses and PD patients differed signifi cantly from all other groups when off L-dopa. ACs improved the motor control mechanisms used for obstacle crossing in people with PD. These results support the notion that external AC therapy may be used as a complement to drug therapy tohelp improve locomotion in PD patients, even on complex tasks such as obstacle crossing.

Auditory cues assist patients with Parkinson’s disease (on and off L-dopa) during obstacle crossing

People with Parkinson’s disease (PD) have an impaired locomotor pattern. As a result, the capacity of walking independently and the interaction with the environment can be impairment. Uneven environments can challenge even more the motor control of these patients to perform the locomotor tasks successfully. Besides of the levodopa therapy, the auditory cues have also been utilized to improve the gait parameters. However, the effects of auditory cues in gait during obstacle avoidance and the association with the levodopa effects are not known. The aim of this study was to investigate the effects of AC during obstacle crossing in people with PD (on and off L-dopa) and in healthy control participants.A total of 30 individuals participated in the study, including 15 PD patients who were tested both on and off L-dopa and 15 healthy adult controls. The task consisted of stepping over an obstacle located in the middle of the path under two conditions, i.e., cued and non-cued. We used kinematic, kinetic and electromyographic analyses to evaluate individuals' locomotor patterns. Groups differed signifi cantly from each other for all analyses and PD patients differed signifi cantly from all other groups when off L-dopa. ACs improved the motor control mechanisms used for obstacle crossing in people with PD. These results support the notion that external AC therapy may be used as a complement to drug therapy tohelp improve locomotion in PD patients, even on complex tasks such as obstacle crossing.

Autonomous Stair Climbing for a High-Performance Wheelchair that Realizes Standing and Traveling on Uneven Environments

Autonomous Stair Climbing for a High-Performance Wheelchair that Realizes Standing and Traveling on Uneven Environments

결합 가능한 모듈형 4족 로봇의 설계 및 작업 계획에 대한 연구

최근 다양한 환경에서 지능형 로봇의 안정된 이동과 작업계획에 대한 연구가 이루어지고 있다. 본 논문에서는 상하 결합가능한 구조의 4족 로봇의 설계 및 작업 계획방법을 제안한다. 제안하는 4족 로봇은 리니어 모터를 이용하여 다리 길이를 조절하고, 팔각뿔 형태의 도킹모듈을 이용하여 상하 결합과 분리가 가능하도록 설계하였다. 또한 로봇이 다양한 환경에서 안정된 이동과 정보 수집을 위하여 지자기 센서, PSD 센서, LRF 센서와 카메라를 사용하였다. 리니어 모터를 이용한 장애물 회피 동작방법과 상하 결합 동작방법을 제안하고 구현하였다. 로봇은 다리 길이를 조절하여 장애물을 극복하고, 두 대의 로봇이 상하 결합을 통하여 협력 작업방법을 제안하였다. 두 대의 4족 로봇이 상하 결합을 통하여 4족과 6족 보행을 하고, 상부 결합 로봇의 4개의 다리를 4개의 팔 또는 2개의 팔로 사용할 수 있으며, 결합된 로봇을 이용하여 물건 옮기기 작업을 구현하고, 각 동작들을 실제 실험으로 기능을 검증하였다. There are many researches to develop robots that improve its mobility and task planning to adapt in various uneven environments. In this paper, we propose the design method and task planning of quadruped robot which can have top-bottom docking structure. The proposed quadruped robot is designed to adjust leg length using linear actuators and perform top-bottom docking and undocking using octagonal cone shaped docking module. Also, to stable walking and information gathering in the various environments, a geomagnetic sensor, PSD sensor, LRF sensor and camera. We propose an obstacle avoidance method and the topbottom docking algorithm of the two quadruped robots using linear actuator. The robot can overcome obstacles using adjusting leg length and activate the top-bottom docking function. The top-bottom docking robots of two quadruped robot can walk 4 legged walking and 6 legged walking, and use 4 arms or 2 arms the upper. We verified that the docking robots can carry objects using 4 leg of the upper robot.

Wave Equalization - A New Image Enhancement Method for Gray Image Binarization under Uneven Illumination

The gray image can be viewed as a 3D terrain consisting of intensity waves. The Wave Equalization introduced in the paper is to weaken the influence of uneven illumination on the gray image binarization. The 2D wave is decomposed into several 1D waves corresponding to different directions for 1D equalization. Then PCA algorithm is used to compress all 1D results to the final image with uniform illumination. The extensive experiments in the paper had proved that our method has excellent performance and adaptability for various uneven illumination environments.

1A1-C01 立位・不整地移動を可能にする高機能電動車いす(福祉ロボティクス・メカトロニクス(1))

This paper proposes an electric wheelchair that realized traveling on uneven environments and standing. The proposed wheelchair allows a caregiver to reduce their burdens and a user to improve QOL. Conventional electric wheelchairs have mainly three problems: medical problems sitting for a long time, a psychological problem due to the low position of eyes, and low traveling performances on uneven environments. The proposed wheelchair consists of a link mechanism powered by a gas spring for changing its posture and a traveling mechanism with a part of caterpillar and a flipper arm for uneven environments. This paper presents the concept design and the experimented results of standing and stair climbing using a scale model wheelchair, which confirms the design effectiveness.

Perception of effective contact area distribution for humanoid robot foot

Maintaining dynamical stability for humanoid robots to walk or run in even environments has so far been achieved. However, it will become a challenge work to keep balance under rough terrains, because the effective contact area (ECA) between the feet and the uneven environments is less than that on even ground. Thus some control schemes are additionally needed for robot to keep dynamical balance, which increases the complexity of control. In view of that, flexible force sensor array (FFSA) system is adopted under robot feet to detect the ECA in the case of stepping on rough terrains. Structure optimum, data acquisition, processing methods, etc., of the FFSA system are all elaborately provided in this paper. And the feasibility and validity of the FFSA system mounted in the robot foot system are experimentally tested on the humanoid robot platform BHR-2.

복합 바퀴-다리 이동형 로봇의 저전력 보행 기반 장애물 회피 알고리즘

최근 다양한 환경에서 지능형 로봇의 안정된 이동방법에 대한 연구가 활발히 이루어지고 있다. 본 논문에서는 복합 바퀴-다리형 이동 로봇의 설계 방법을 제안하고, LRF(Laser Range Finder)센서를 이용한 복합 이동형 로봇의 저전력 보행 기반 장애물 회피 알고리즘을 제안하였다. 로봇의 자세 안정화와 소비에너지를 줄이기 위해 모터 전류값을 바탕으로 자세를 보정하여 저전력 보행 알고리즘을 구현하였고, 이를 기반으로 LRF센서를 이용한 장애물 회피 알고리즘을 제안하였다. 로봇의 각 다리에서 소비되는 전력을 고르게 분포시키게 자세를 보정하여 보행을 안정화시키고, 최단 경로로 장애물을 회피하여 이동함으로써 전체 소비 에너지를 감소시키며 보행 안정성을 향상하였다. 본 연구에서 제안한 방법들은 실제 복합 이동 로봇의 보행 및 장애물 회피 실험을 통해 성능을 검증하였다. There are many researches to develop robots that improve its mobility to adapt in various uneven environments. In the paper, a hybrid wheeled and legged mobile robot is designed and a obstacle avoidance algorithm is proposed based on low power walking using LRF(Laser Range Finder). In order to stabilize the robot's motion and reduce energy consumption, we implement a low-power walking algorithm through comparison of the current value of each motors and correction of posture balance. A low-power obstacle avoidance algorithm is proposed by using LRF sensor. We improve walking stability by distributing power consumption and reduce energy consumption by selecting a shortest navigation path of the robot. The proposed methods are verified through walking and navigation experiments with the developed hybrid robot.

DEVELOPMENT OF AN INTEGRATED PERCEPTUAL FOOT SYSTEM FOR HUMANOID ROBOTS

The realization of dynamic and stable walking anthropomorphically for humanoid robots to step on various kinds of uneven environments has long been considered as the research emphasis in the field of humanoid robot. The foot system constitutes the element which ensures the interaction between the humanoid robot and the environment. Apart from supporting the whole weight of robot and sensing the external forces exerted by the foot system on the ground during walk, perception of effective contact area (ECA) and foot postures are indispensably important information supports for various control schemes. This paper describes our research efforts aimed at an integrated perceptual foot (IPF) system which is designed by the conception derived from human foot motion mechanism. The IPF system possesses the capability to perceive the external forces/torques, ECA distribution, foot postures, zero moment point trajectory and topography conditions, etc. And the feasibility and validity of each sensor system in IPF system are experimentally tested on the humanoid robot platform BHR-2, which provide useful information support as possible to achieve some new and effective control schemes for humanoid robots.

결합 가능한 복합 바퀴-다리 이동형 로봇에 관한 연구

There are many researches to develop robots that improve its mobility to adapt in various uneven environments. In the paper, a hybrid mobile robot that can dock with the other robot and transforms between wheeled robot and legged robot is proposed. The hybrid mobile robot platform has docking device with a peg and a cup module. In addition, the robot is possible to walk and drive according to condition of the road. A navigation algorithm of the hybrid mobile robot is proposed to improve the mobility of robots using docking algorithm based on image processing on the broken road and uneven terrain. The proposed method recognizes road condition through PSD sensor attached in front and bottom of the robot and selects an appropriate navigation method according to terrain surface. The proposed docking and navigation methods are verified through experiments using hybrid mobile robots.

Hierarchical Fuzzy Motion Planning for Humanoid Robots Using Locomotion Primitives and a Global Navigation Path

This paper presents a hierarchical fuzzy motion planner for humanoid robots in 3D uneven environments. First, we define both motion primitives and locomotion primitives of humanoid robots. A high-level planner finds a global path from a global navigation map that is generated based on a combination of 2.5 dimensional maps of the workspace. We use a passage map, an obstacle map and a gradient map of obstacles to distinguish obstacles. A mid-level planner creates subgoals that help the robot efficiently cope with various obstacles using only a small set of locomotion primitives that are useful for stable navigation of the robot. We use a local obstacle map to find the subgoals along the global path. A low-level planner searches for an optimal sequence of locomotion primitives between subgoals by using fuzzy motion planning. We verify our approach on a virtual humanoid robot in a simulated environment. Simulation results show a reduction in planning time and the feasibility of the proposed method.

3자유도 결합 팔을 가진 모듈형 로봇의 비평탄 지형 주행 알고리즘

본 논문에서는 미지 환경의 비평탄 지형에서 로봇 주행에 제한이 따르는 문제를 극복하기 위해 물리적 결합을 통한 모듈형 로봇의 이동성 향상 기법을 제안한다. 모듈형 로봇 시스템은 자가 결합 기구 장치, 3자유도 로봇 결합 팔, 모듈 로봇 플랫폼, 모션제어기, 주제어기로 구성하였으며, 로봇간 결합 및 협업을 위해 RGGR구조의 결합 메카니즘을 사용하였다. 또한 실내 GPS를 사용하여 로봇의 실시간 위치 및 진행 방향을 추정하고, 추정된 정보를 기반으로 로봇의 이동 경로와 방향을 제어하여 로봇간 물리적 결합을 수행하였다. 물리적 결합을 통한 모듈형 로봇의 비평탄 지형 주행 알고리즘의 성능을 검증하기 위해 세 대의 모듈형 로봇을 제작하여 실제 끊어진 도로와 단턱이 존재하는 환경에서 실험을 통해 검증하였다. In the paper, we propose an improved mobility method of modular robots by physical docking in the uneven environments. The modular robot system consists of autonomous docking device, 3 DOF robotic arm, motion controller, and main controller. Real-time location and direction of the robot are estimated using inner GPS and they are used to control direction and path of each robot for physical docking between modular robots. We design a navigation algorithm of modular robot using physical docking and cooperative navigation in the environment with broken road and low stair. The proposed method is verified by navigation experiments of three developed modular robots in the uneven environments.