Comparison of Different Approaches to Vibration-based Terrain Classification
نویسندگان
چکیده
There is a variety of different terrain types in outdoor environments, each posing different dangers to the robot and demanding a different driving style. In a previous paper, we presented a terrain classification method based on Support Vector Machines (SVM), which uses vibrations induced in the body of the robot to learn different terrain classes. However, in the previous paper, our experimental results were based on vibration data collected by a hand-pulled cart with relatively hard wheels. In this paper, we present experiments on data collected by our RWI ATRV-Jr outdoor robot. Additionally, we compare our SVM-based method to alternative classification methods. The comparison shows that our approach outperforms the other methods.
منابع مشابه
A Comparison of Classifier Performance for Vibration-based Terrain Classification
The ability to recognize the encountered terrain is an essential part of any terrain-dependent control system designed for mobile robots. Terrains such as sand and gravel make vehicle mobility more difficult and thus reduce vehicle performance. To alleviate this problem the vehicle control system can be tuned for maximum speeds, turning angles, accelerations and other conditions to help adapt t...
متن کاملAnalysis of the dynamic behavior of the car user in the irregular terrain
Many people experience vibration effects on whole-body throughout their lives frequently. Vibrating energy absorbed is exposed all-body caused with vibration hazard in the vertically on body and biodynamic responses from body in speed 2.37 to 5.14 m/s could captivate with car seat on user body, so the vibration energy transferred to a seated people body. In this paper, the human body is modeled...
متن کاملTerrain Classification Using Vibration Sensors: Theory and Methods
To improve the response of an autonomous ground vehicle (AGV) as it seeks to complete an outdoor mission, the control system of the vehicle should vary as it encounters specific terrains such as sand, gravel, mud, or ice. To determine when to switch the control system it is beneficial to have accurate and fast online terrain classification. The earliest terrain classification algorithms were vi...
متن کاملProposing a Novel Cost Sensitive Imbalanced Classification Method based on Hybrid of New Fuzzy Cost Assigning Approaches, Fuzzy Clustering and Evolutionary Algorithms
In this paper, a new hybrid methodology is introduced to design a cost-sensitive fuzzy rule-based classification system. A novel cost metric is proposed based on the combination of three different concepts: Entropy, Gini index and DKM criterion. In order to calculate the effective cost of patterns, a hybrid of fuzzy c-means clustering and particle swarm optimization algorithm is utilized. This ...
متن کاملSVMs for Vibration-Based Terrain Classification
When an outdoor mobile robot traverses different types of ground surfaces, different types of vibrations are induced in the body of the robot. These vibrations can be used to learn a discrimination between different surfaces and to classify the current terrain. Recently, we presented a method that uses Support Vector Machines for classification, and we showed results on data collected with a ha...
متن کامل