자율이동로봇의 상대 위치, 선형/회전 속도를 얻기 위한 가장 기본적인 Dead Reckoning 항법시스템은 엔코더를 기반으로 한다. 엔코더 기반의 항법시스템은 이론적으로 단순하여 구현이 용이하고 관리가 쉬울 뿐만 아니라, 가격이 저렴하다는 장점을 갖고 있어 가장 널리 ...

자율이동로봇의 상대 위치, 선형/회전 속도를 얻기 위한 가장 기본적인 Dead Reckoning 항법시스템은 엔코더를 기반으로 한다. 엔코더 기반의 항법시스템은 이론적으로 단순하여 구현이 용이하고 관리가 쉬울 뿐만 아니라, 가격이 저렴하다는 장점을 갖고 있어 가장 널리 사용되고 있다. 그러나 바퀴의 미끄러짐 현상과 같은 운동에 미치는 외부 소스를 관측하지 못하는 한계로 인하여, 항법오차는 시간에 따라 증가하는 결정적인 단점을 갖고 있다.
본 연구에서는, 이동 로봇의 회전 각도를 정밀 측정하기 위하여 레이트 자이로 센서 만으로 요우각을 추정하는 기법을 연구한다. 이를 위한 세부 연구내용은 다음과 같다.

■ 자이로 파라미터 식별을 위한 정밀 실험/파라미터 추출
Thermal Chambered Rate Table과 방진 Table을 이용하여 아래와 같은 실험 절차를 정립하고 이를 통하여 자이로 파라미터를 정량적으로 추출한다. 한편, 이 결과를 자율로봇에 적용이 적합한 자이로를 선정하기 위한 기본 자료로 삼는다.
- Stability Test (Bias Stability, Angle Random Walk)
- Rate Transfer Test (Scale Factor Error)
- Thermal Test (Bias Stability, Scale Factor Stability)

■ 최소 Dfift 방위각 측정시스템 개발
일반적으로 MEMS 자이로는 저 사양의 확정적 및 확률적 오차특성을 갖고 있으며, 방위각을 얻기 위한 적분 과정에서 필연적으로 발산하는 결과를 초래하게 된다. 따라서 장시간 정밀도 유지를 위해서는 정밀한 보정 절차가 필수적이다. 본 연구에서는 채택된 MEMS 자이로를 사용하여 방위각을 추정하고 자체적으로 그 오차를 보정하기 위한 알고리즘을 연구하여 장시간 운용이 가능한 스트랩다운 방위각 측정시스템 개발을 목표로 한다. 이를 위한 세부연구 결과는 다음과 같다.
- 자이로 주요 오차 모델링
- 자체 온라인 보정기법 연구
- 운용 및 환경 조건에 따른 필터링 기법 연구

Less expensive self-localization of the robot is one of the most important problems in popularizing autonomous service robot products. However, trade-offs exist between making less expensive self-localization systems and the quality at which they perf ...

Less expensive self-localization of the robot is one of the most important problems in popularizing autonomous service robot products. However, trade-offs exist between making less expensive self-localization systems and the quality at which they perform. Relative localizations that utilize low-cost gyroscope (hereafter refer to as a gyro) based on technology referred to as Micro Electro-Mechanical System (MEMS) with odometry sensors have emerged as standalone, and robust to environment changes. However, the performance characteristics associated with these low-cost MEMS gyros are limited by various error sources that affect long-term and short-term performance, such as the bias/scale-factor error and the Angle Random Walk (ARW), respectively. Due to the numeric integration process of angular velocity (rate) output of a gyro for the angle estimation purposes, gyros are usually required to meet the high performance demands. Otherwise, the accumulated angular error grows considerably over time and provides a fundamental limitation to any angle measurement that relies solely on integration of rate. Therefore self-localization of a robot with unaided (without odometer/velocity or GPS or magnetometer aiding) low-cost MEMS gyro is still a challenging problem.

To achieve the challenges of low-cost MEMS gyros, this study examines an effective method of minimizing drift on the heading angle that relies solely on integration of rate signal getting over major sources of error. This method can be extended to fur-ther reduce the localization error in cooperation with absolute localization method that uses external beacons or landmarks as well as relative one that uses internal odometry sensors. The main idea of the proposed approach is consists of two parts. First, during startup, time-varying calibration coefficients of both ‘scale factor error’ and ‘bias’ are simultaneously estimated online and stored. Subsequently, when a gyro measurement is taken, it is compensated with the estimated coefficients. This means that the calibration coefficients that affect long-term performance are updated regularly so that the performance is kept consistent regardless of aging. The second part employed is to threshold the output from the compensated gyro signal. That is, the broadband noise components at the gyro output (ARW) which lie under a certain threshold value are filtered out and set to zero. This means that the ARW that affects the short-term performance is partially rejected when there’s no turning mo-tion.

An EPSON XV3500 MEMS gyro was selected as the candidates for this study. It has performance indexes of 18°/hr bias stability, 2.5°/√hr ARW. These specifications are saying that, if we integrate the signals of this gyro for 30 minutes (assumed cleaning robot’s operating time) it can be supposed to have the standard deviation of the distribution of the angle drift up to 11°, which provides a fundamental limitation to any angle measurement that relies solely on integration of rate. However, experimental results with the proposed phased method applied to XV3500 demonstrate that it effectively yields minimal-drift angle measurements getting over major error sources that affect both long-term and short-term performance.

This study organized as follows.
- Section 2 describes the performance characteris-tics for the gyroscope XV3500 through experimental tests.
- In Section 3, the algo-rithms for minimal-drift heading angle measurement including online self-calibration with least square algorithm and threshold filter are presented.
- In Section 4, the expe-rimental results are provided to demonstrate the effectiveness of the proposed phased method.
- Concluding remarks are given in Section 5.

To achieve the challenges of low-cost MEMS gyros for the precise self-localization of autonomous robots, this paper examines an effective method of minimizing drift on the heading angle that relies solely on integration of rate signals from a gyro. Th ...

To achieve the challenges of low-cost MEMS gyros for the precise self-localization of autonomous robots, this paper examines an effective method of minimizing drift on the heading angle that relies solely on integration of rate signals from a gyro. The main idea of the proposed approach is consists of two parts; 1) self-identification of calibration coefficients that affects long-term per-formance, and 2) threshold filter to reject the broadband noise component that affects short-term performance. Experimental results with the proposed phased method applied to Epson XV3500 gyro demonstrate that it effectively yields minimal drift heading angle measurements getting over major error sources in the gyro output.

To achieve the challenges of low-cost MEMS gyros for the precise self-localization of mobile robots, this paper examines an effective method of minimizing drift on the heading angle that relies solely on integration of rate signals from a gyro. The ma ...

To achieve the challenges of low-cost MEMS gyros for the precise self-localization of mobile robots, this paper examines an effective method of minimizing drift on the heading angle that relies solely on integration of rate signals from a gyro. The main idea of the proposed approach is consists of two parts; 1) self-identification of calibration coefficients that affects long-term performance, and 2) threshold filter to reject the broadband noise component that affects short-term performance. Experi-mental results with the proposed phased method applied to Epson XV3500 gyro demonstrate that it effectively yields minimal drift heading angle measurements getting over major error sources in the gyro output. We suggest that the gyro can be used in a wide range of mobile robotic applications, both as a "global reference" but also to help odometry, with extension of proposed method to further reduce the localization error.