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In view of the large randomness, redundant path nodes, and low search efficiency of RRT-connect in a complex obstacle environment, this study intends to develop a path-planning method combining RRT-connect and Informed RRT*. First, to solve the problem of large sampling randomness, the Informed RRT* algorithm is combined to adopt a simpler rectangle and limit the sampling range to the rectangle. Second, for the poor quality of the search path, the dynamic step size is used for growth extension, the reverse greedy algorithm is used to delete redundant nodes, the spline curve is used to smooth the path such that the position meets the cubic spline curve and the speed meets the quadratic spline curve, and the final path is optimized. Finally, the proposed algorithm is verified in the simulation and real world using a self-developed quadrupedal robot. Compared with the original RRT-connect algorithm, the first solution time, total number of nodes, and initial path cost were reduced by more than 11%, 8.5%, and 2.5%, respectively.

The sampled rectangular pulse consists of an ideal noiseless rectangular pulse plus additive Gaussian white noise (AGWN). A rectangular pulse is optimally integrated when the integration aperture is perfectly matched to the pulse: it has the same duration as the pulse and is synchronized with it in the obvious way. If the aperture starts before the pulse or ends after it, extra noise is acquired and the signal‐to‐noise ratio (SNR) declines from the optimum. Digital integration and averaging are discussed, relevant signal processing definitions are presented, and noise bandwidth is defined and used. The effects of sampling frequency, area fraction integrated, and pulse‐to‐pulse fluctuations are discussed. A commonly encountered chemical measurement system (CMS) with p‐p fluctuation noises is that of the scanning fluorimeter: even with constant fluorophore content, p‐p fluctuations in the excitation light source cause p‐p fluctuations in the signal response, but not necessarily the background response.