RGB-D cameras (or color-depth cameras) play key roles in many vision applications. A typical RGB-D camera has only rough intrinsic and extrinsic calibrations that cannot provide the accuracy required in many vision applications. In this paper, we propose a novel and accurate sphere-based calibration framework for estimating the intrinsic and extrinsic parameters of color-depth sensor pair. Additionally, a method of depth error correction is suggested, and the principle of error correction is analyzed in detail. In our method, the feature extraction module can automatically and reliably detect the center and edges of the sphere projection, while excluding noise data and outliers, and the projection of the sphere center on RGB and depth images is used to obtain a closed solution of the initial parameters. Finally, all the parameters are accurately estimated within the framework of nonlinear global minimization. Compared to other state-of-the-art methods, our calibration method is easy to use and provides higher calibration accuracy. Detailed experimental analysis is performed to support our conclusions.
With the rapid development of robot perception and planning technology, robots are gradually getting rid of fixed fences and working closely with humans in shared workspaces. The safety of human-robot coexistence has become critical. Traditional motion planning methods perform poorly in dynamic environments where obstacles motion is highly uncertain. In this paper, we propose an efficient online trajectory generation method to help manipulator autonomous planning in dynamic environments. Our approach starts with an efficient kinodynamic path search algorithm that considers the links constraints and finds a safe and feasible initial trajectory with minimal control effort and time. To increase the clearance between the trajectory and obstacles and improve the smoothness, a trajectory optimization method using the B-spline convex hull property is adopted to minimize the penalty of collision cost, smoothness, and dynamical feasibility. To avoid the collisions between the links and obstacles and the collisions of the links themselves, a constraint-relaxed links collision avoidance method is developed by solving a quadratic programming problem. Compared with the existing state-of-the-art planning method for dynamic environments and advanced trajectory optimization method, our method can generate a smoother, collision-free trajectory in less time with a higher success rate. Detailed simulation comparison experiments, as well as real-world experiments, are reported to verify the effectiveness of our method.
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