3D Object Pose Estimation Using Chamfer Matching and Flexible CAD File Base

Estimating the object pose is an interesting topic in the industrial robotic vision field. By having an accurate result for detecting object pose, it means the system performs the task as the target in the bin-picking technique. The methods which are developed are varies widely. But the challenge for this paper is estimating a 3D object using mono camera accurately. The object which is used in this paper has the symmetric rotational shape, in this case is the sprayer. In this paper, the camera uses a tool from the Blender Software, such that the ground truth is measurable and it will be the reference for calculating the error. The applied algorithms of this paper are Border Line Extraction Algorithm utilized in the template generation step as the reference template, Directional Chamfer Matching for detecting the coarse pose, and Lavenberg-Marquardt Method to optimize the object pose result. The result achieves the average error of the coarse pose for x and y position (translation pose) are 2.05 mm and 0.71 mm. Meanwhile for the optimized pose, the average error for x and y position (translation pose) are 1.82 mm and 0.24 mm. Regarding the rotational pose, the average error of the rotational coarse pose with respect to x and z axis are 0.01 degree and 0.45 degree. Whereas the average error of the rotational optimized pose with respect to x and z axis are 2.88 degree and 0.82 degree

Super Twisting Sliding Mode Control with Region Boundary Scheme for an Autonomous Underwater Vehicle

A robust tracking control for an Autonomous Underwater Vehicle (AUV) system operated in the extreme ocean environment activities is very much needed due to its external disturbances potentially disturb the stability of the system. This research proposes a new robust-region based controller which integrates Super Twisting Sliding Mode Control (STSMC) with region boundary approach in the presence of determined disturbances. STSMC is a second order SMC which combines between continuous signal and discontinuous signal to produce a robust system. By incorporating region based control into STSMC, the desired trajectory defined as a region produces an energy saving control compared to conventional point based control. Energy function of region error is applied on the AUV to maintain inside the desired region during tracking mission, thus, minimizing the energy usage. Analysis on a Lyapunov candidate proved that the proposed control achieved a global asymptotic stability and showed less chattering, providing 20s faster response time to handle perturbations, less transient of thrusters\u27 propulsion and ability to save 50% of energy consumption compared to conventional SMC, Fuzzy SMC and STSMC. Overall, the newly developed controller contributed to a new robust, stable and energy saving controller for an AUV in the presence of external disturbances

Robust-formation control of multi-autonomous underwater vehicles based on consensus algorithm

This paper discusses a robust formation control for multi-Autonomous Underwater Vehicles (AUVs). The AUVs are disturbed by exogenous perturbation during the mission, thus, the Robust Integral Sign of Error (RISE) is adopted. For a formation control, a leader-follower structure based on consensus algorithm is adopted and the use of graph theorem named connected graph is useful to exchange the required information. An AUV called leader is determined to bring a group of information, while the others called followers, receive the information from a leader. Lyapunov analysis proves the stability as well as the error convergence of proposed controller, whilst some simulations are performed to compare between the proposed controller, RISE with consensus, and the existing robust controller, Sliding Mode Controller (SMC) which is combined with consensus algorithm. As a result, the proposed controller works better and produces smaller error