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1

Stability Controller on the Atlas Robot Example

Wasielica M.

Pomiary Automatyka Robotyka

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2017

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R. 21, nr 2

65--70

EN

The paper presents the gait framework for a biped robot on the Atlas robot example. The method utilizes inverted pendulum model and static stability controller with correction from IMU sensor. A straight-forward balance control strategy based on ankle joints control is proposed. The controller which stabilizes the robot during execution of the planned path is described. To show the efficiency of the proposed method the results obtained in the Virtual Robotics Challenge environment (Gazebo) are provided.

PL

Artykuł przedstawia system generowania chodu dla robotów dwunożnych na przykładzie robota Atlas. Metoda wykorzystuje model odwróconego wahadła oraz statyczny kontroler stabilności wraz z korekcją z sensora IMU. Zaproponowano prostą metodę utrzymywania równowagi w oparciu o sterowanie ruchami stóp robota. Opisano też kontroler stabilizujący robota podczas pokonywania zaplanowanej ścieżki. Zweryfikowano działanie zaproponowanych metod na robocie Atlas w symulatorze Virtual Robotics Challenge (Gazebo).

2

RGB-D terrain perception and dense mapping for legged robots

Belter D., Łabecki P, Fankhauser P., Siegwart R.

International Journal of Applied Mathematics and Computer Science

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2016

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Vol. 26, no. 1

81--97

EN

This paper addresses the issues of unstructured terrain modeling for the purpose of navigation with legged robots. We present an improved elevation grid concept adopted to the specific requirements of a small legged robot with limited perceptual capabilities. We propose an extension of the elevation grid update mechanism by incorporating a formal treatment of the spatial uncertainty. Moreover, this paper presents uncertainty models for a structured light RGB-D sensor and a stereo vision camera used to produce a dense depth map. The model for the uncertainty of the stereo vision camera is based on uncertainty propagation from calibration, through undistortion and rectification algorithms, allowing calculation of the uncertainty of measured 3D point coordinates. The proposed uncertainty models were used for the construction of a terrain elevation map using the Videre Design STOC stereo vision camera and Kinect-like range sensors. We provide experimental verification of the proposed mapping method, and a comparison with another recently published terrain mapping method for walking robots.

3

Interactive programming of a humanoid robot

Wasielica M., Wąsik M., Kasiński A.

Journal of Automation Mobile Robotics and Intelligent Systems

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2014

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Vol. 8, No. 3

3--9

EN

This paper presents a control system for a humanoid robot based on human body movement tracking. The system uses the popular Kinect sensor to capture the mo- tion of the operator and allows the small, low-cost, and proprietary robot to mimic full body motion in real time. Tracking controller is based on optimization-free algorithms and uses a full set of data provided by Kinect SDK, in order to make movements feasible for the considerably different kinematics of the humanoid robot compared to the human body kinematics. To maintain robot stability we implemented the balancing algorithm based on a simple geometrical model, which adjusts only the configuration of the robot’s feet joints, maintaining an unchanged imitated posture. Experimental results demonstrate that the system can successfully allow the robot to mimic captured human motion sequences.

4

A biologically inspired approach to feasible gait learning for a hexapod robot

Belter D., Skrzypczyński P.

International Journal of Applied Mathematics and Computer Science

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2010

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Vol. 20, no 1

69-84

EN

The objective of this paper is to develop feasible gait patterns that could be used to control a real hexapod walking robot. These gaits should enable the fastest movement that is possible with the given robot's mechanics and drives on a flat terrain. Biological inspirations are commonly used in the design of walking robots and their control algorithms. However, legged robots differ significantly from their biological counterparts. Hence we believe that gait patterns should be learned using the robot or its simulation model rather than copied from insect behaviour. However, as we have found tahula rasa learning ineffective in this case due to the large and complicated search space, we adopt a different strategy: in a series of simulations we show how a progressive reduction of the permissible search space for the leg movements leads to the evolution of effective gait patterns. This strategy enables the evolutionary algorithm to discover proper leg co-ordination rules for a hexapod robot, using only simple dependencies between the states of the legs and a simple fitness function. The dependencies used are inspired by typical insect behaviour, although we show that all the introduced rules emerge also naturally in the evolved gait patterns. Finally, the gaits evolved in simulations are shown to be effective in experiments on a real walking robot.