scholarly journals How biomechanics, path planning and sensing enable gliding flight in a natural environment

2020 ◽  
Vol 287 (1921) ◽  
pp. 20192888
Author(s):  
Pranav C. Khandelwal ◽  
Tyson L. Hedrick

Gliding animals traverse cluttered aerial environments when performing ecologically relevant behaviours. However, it is unknown how gliders execute collision-free flight over varying distances to reach their intended target. We quantified complete glide trajectories amid obstacles in a naturally behaving population of gliding lizards inhabiting a rainforest reserve. In this cluttered habitat, the lizards used glide paths with fewer obstacles than alternatives of similar distance. Their takeoff direction oriented them away from obstacles in their path and they subsequently made mid-air turns with accelerations of up to 0.5 g to reorient towards the target tree. These manoeuvres agreed well with a vision-based steering model which maximized their bearing angle with the obstacle while minimizing it with the target tree. Nonetheless, negotiating obstacles reduced mid-glide shallowing rates, implying greater loss of altitude. Finally, the lizards initiated a pitch-up landing manoeuvre consistent with a visual trigger model, suggesting that the landing decision was based on the optical size and speed of the target. They subsequently followed a controlled-collision approach towards the target, ending with variable impact speeds. Overall, the visually guided path planning strategy that enabled collision-free gliding required continuous changes in the gliding kinematics such that the lizards never attained theoretically ideal steady-state glide dynamics.

Mathematics ◽  
2021 ◽  
Vol 9 (15) ◽  
pp. 1821
Author(s):  
Lazaros Moysis ◽  
Karthikeyan Rajagopal ◽  
Aleksandra V. Tutueva ◽  
Christos Volos ◽  
Beteley Teka ◽  
...  

This work proposes a one-dimensional chaotic map with a simple structure and three parameters. The phase portraits, bifurcation diagrams, and Lyapunov exponent diagrams are first plotted to study the dynamical behavior of the map. It is seen that the map exhibits areas of constant chaos with respect to all parameters. This map is then applied to the problem of pseudo-random bit generation using a simple technique to generate four bits per iteration. It is shown that the algorithm passes all statistical NIST and ENT tests, as well as shows low correlation and an acceptable key space. The generated bitstream is applied to the problem of chaotic path planning, for an autonomous robot or generally an unmanned aerial vehicle (UAV) exploring a given 3D area. The aim is to ensure efficient area coverage, while also maintaining an unpredictable motion. Numerical simulations were performed to evaluate the performance of the path planning strategy, and it is shown that the coverage percentage converges exponentially to 100% as the number of iterations increases. The discrete motion is also adapted to a smooth one through the use of B-Spline curves.


Author(s):  
Ho-Hoon Lee

This paper proposes a path planning strategy for high-performance anti-swing control of overhead cranes, where the anti-swing control problem is solved as a kinematic problem. First, two anti-swing control laws, one for hoisting up and the other for hoisting down, are proposed based on the Lyapunov stability theorem. Then a new path-planning strategy is proposed based on the concept of minimum-time control and the proposed anti-swing control laws. The proposed path planning is free from the usual constraints of small load swing, slow hoisting speed, and small hoisting distance. The effectiveness of the proposed path planning is shown by computer simulation with high hoisting speed and hoisting ratio.


Author(s):  
Sumedh Ghogare ◽  
S. S. Pande

This paper reports the development of an efficient iso-scallop tool path planning strategy for machining of freeform surfaces on a three axis CNC milling center using the point cloud as the input. Boundary of the point cloud is chosen as the Master Cutter Path, using which the scallop points are computed. Adjacent side tool paths are computed using these scallop points and the path planning process is completed till the entire surface is covered. The system generates post-processed NC program in ISO format which was extensively tested for various case studies. The results were compared with the iso-planar tool path strategy from commercial software. Our system was found to generate efficient tool path in terms of part quality, productivity and storage memory.


2022 ◽  
Author(s):  
Ryunosuke Harada ◽  
Hiroshi Yoshitake ◽  
Motoki Shino

Abstract To ensure the coexistence of autonomous personal mobility vehicles (PMVs) and pedestrians in a pedestrian zone, they should be able to smoothly pass across and avoid each other. Studies suggest that it is possible that PMVs and pedestrians can pass each other in a short period of time without compromising their comfort; this can be achieved through understanding how pedestrians react to the behavior of PMVs and by modifying the autonomous navigation of PMVs accordingly. Therefore, in this study, the avoidance behavior characteristics of pedestrians were investigated. Experiments were conducted to understand the influence of the selected avoiding behavior parameters and to understand the behavior characteristics of pedestrians in relation to the behavior of PMVs. Furthermore, a path planning strategy that enables smooth passing was developed based on these characteristics. The usefulness of this method was evaluated. The avoidance time and the avoiding angular velocity at the start and end of the avoidance behavior were the parameters that contributed to smooth autonomous navigation. The results show that pedestrian tolerance improves and the avoidance width decreases depending on these parameters. Furthermore, smooth autonomous navigation can be achieved using the characteristics of pedestrians’ cognition against PMVs.


2019 ◽  
Vol 9 (2) ◽  
pp. 26-39 ◽  
Author(s):  
Helmuth Yesid Arias Gómez ◽  
Gabriela Antošová

AbstractThe article explores the natural context and the geographical conditions for developing tourism and for designing sectorial plans. The objective is to offer basic visual rendering as a resource for appreciating the natural environs in which the tourist activity evolves and use such resource as useful input during the planning and designing exercises. The methodology relies on the application of cartographic and spatial tools as instruments for recognising the territory and the natural landscape. The results render the current condition of natural resources and the territorial reality, as a general frame for proposing sustainable strategies of tourism planning. The contribution of the analysis can be appreciated amid the scarcity of local and specific cartographic analysis, and the precarious stock of inputs that could guide the tourism and the territorial planning in lagged territories. An overwhelming conclusion of our exercise is that the awarness and valuations of natural endowments are key elements for preserving the environment and for applying an adequate planning strategy in order to reconcile the economic necessities and the preservation of natural environment.


2016 ◽  
Vol 16 (4) ◽  
pp. 113-125
Author(s):  
Jianxian Cai ◽  
Xiaogang Ruan ◽  
Pengxuan Li

Abstract An autonomous path-planning strategy based on Skinner operant conditioning principle and reinforcement learning principle is developed in this paper. The core strategies are the use of tendency cell and cognitive learning cell, which simulate bionic orientation and asymptotic learning ability. Cognitive learning cell is designed on the base of Boltzmann machine and improved Q-Learning algorithm, which executes operant action learning function to approximate the operative part of robot system. The tendency cell adjusts network weights by the use of information entropy to evaluate the function of operate action. The results of the simulation experiment in mobile robot showed that the designed autonomous path-planning strategy lets the robot realize autonomous navigation path planning. The robot learns to select autonomously according to the bionic orientate action and have fast convergence rate and higher adaptability.


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