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Posture control is one of the fundamental requirements for legged robots to achieve mobility on uneven terrain. Most of the research on posture control is conducted on custom designed robot platforms, which are much more expensive than their commercially available counterparts. This paper presents the implementation of a standing posture control system on a low-cost, commercially available hexapod...
In this work, the Leapfrog algorithm from optimal control is presented as a method for optimal path planning for a mobile robot in the presence of obstacles. The proposed algorithm allows the robot to plan a collision-free path through static obstacles by minimizing a cost functional that includes energy terms and the Gaussian potential function. The Leapfrog path is initialized using the RRT planning...
This work deals with formulating an optimal motion planning problem for a mobile robot in the presence of obstacles using optimal control. For obstacle avoidance, a repulsive potential function defined as a Gaussian function is applied in the cost functional which minimizes the energy control effort. The Leapfrog method numerically solves the formulated optimal control problem. With Leapfrog one...
The use of low-cost, camera sensors for Simultaneous Localization And Mapping and Moving Object Tracking (SLAMMOT) is a developing research area. Image features can be static or dynamic, sparse or dense, and can appear or disappear, making them difficult to track individually over an image sequence. Clustering techniques have been recommended and used to cluster image features to improve tracking...
This paper introduces a state estimation methodology for a hexapod robot that makes use of proprioceptive sensors and a kinematic model of the robot. The methodology focuses on providing reliable full pose state estimation for a commercially-available hexapod robot platform with the use of only commonly-available sensors. The presented methodology provides the derivation of the kinematic model and...
The tracking of moving points in image sequences requires unique features that can be easily distinguished. However, traditional feature descriptors are of high dimension, leading to larger storage requirement and slower computation. In this paper, Principal Component Analysis (PCA) is applied to the 64-Dimension (D) Speeded Up Robust Features (SURF) descriptor to reduce the descriptor dimensionality...
Tracking of multiple bright particles (spots) in fluorescence microscopy image sequences is seen as a crucial step in understanding complex information in the cell. However, fluorescence microscopy generates high a volume of noisy image data that cannot be analysed efficiently by means of manual analysis. In this study we compare the performance of two computer-based tracking methods for tracking...
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