9 results about "Herding" patented technology

An autonomous herding system using a fleet of vehicles to manage and retrieve stray animals, combining technologies from U.S. Patents US 12102060 and US 12153451. The system employs autonomous vehicles equipped with optical-LiDAR sensors, GPS, and machine-learning image recognition to detect and guide strays back to the herd. Vehicles operate in two modes: roundup, for gathering scattered animals, and herding, for maintaining cohesion and directing movement. Positioned in traditional formations (point, swing, flank, drag), they use strategic movements, visual cues, and audio signals to influence herd behavior based on flight zone and point-of-balance principles. A trail boss module coordinates vehicle actions, ensuring efficient herd control. The system includes a battery replacement station for continuous operation, automatically swapping depleted batteries. This integration streamlines livestock management, reducing labor costs while improving animal and handler safety.

The invention discloses a variable pesticide application control system and method based on an improved beetle antennae algorithm for optimizing fuzzy PID (Proportion Integration Differentiation). According to the system, the error between the actual flow and the theoretical flow of the corn and soybean nozzles and the error change rate are obtained to serve as fuzzy PID input, PID parameter correction values are obtained through quantization factor mapping, membership function division and fuzzy rule table reasoning, dynamic adjustment of controller parameters is achieved through scaling factor mapping, and therefore the nozzle flow is accurately adjusted. In order to overcome the defects that traditional fuzzy PID parameters are difficult to set and an optimization algorithm is prone to falling into local optimum, the invention provides an improved beetle antennae optimization method which comprises the steps that Logistic chaos initialization, dynamic step size attenuation, guide direction disturbance and a simulated annealing mechanism are introduced, a multi-index weighted fitness function of a root-mean-square error, overshoot and response time is combined, and the optimal parameter of beetle antennae is obtained. And realizing global optimization. According to the method, the response speed, the control precision and the robustness of the variable pesticide application system are effectively improved.

The utility model provides a bee food harvesting tool, which relates to the technical field of agricultural and pastoral tools, and comprises a cylinder body with a slide hole at the closed end; the rod body penetrates through the sliding hole and is in sliding connection with the sliding hole; the multiple connecting rods are circumferentially distributed in the barrel, and the middles of the connecting rods are rotationally connected to the inner side of the barrel; the linkage mechanism is connected with the rod body and connected with one ends of the multiple connecting rods, and the linkage mechanism can drive the other ends of the multiple connecting rods to be folded when the rod body slides into the barrel body; the multiple clamping pieces are connected with the other ends of the multiple connecting rods respectively, the clamping pieces penetrate through the open end of the cylinder body and are used for clamping bee bread to be harvested in a honeycomb, all bee bread in one honeycomb can be taken out only once through the harvesting tool, the harvesting efficiency is high, harvesting is thorough, and the honeycomb integrity can be guaranteed.

The utility model relates to the field of livestock weighing, in particular to a livestock farm weighing guide device which comprises a guide mechanism. The guide mechanism comprises a bottom plate, a fence and a guardrail; the bottom plate is arranged on the ground; the fences are arranged on the two sides of the bottom plate and seal the space of the two side faces of the bottom plate. One end of the guardrail is rotationally connected with the fence, and the other end of the guardrail can be connected with a livestock exit of a farm. Preferably, a weighing mechanism is arranged at one end, far away from the livestock outlet of the farm, of the guide mechanism; the weighing mechanism comprises a weighing plate and a baffle plate; the weighing plate abuts against the bottom plate. The baffles are arranged on the two sides of the weighing plate and seal the space of the two side faces of the bottom plate. According to the method, the livestock does not need to be forcibly driven manually, the guiding efficiency is greatly improved, a large amount of manpower and time cost are saved, meanwhile, the stress response of the livestock is reduced, the good state of the livestock in the weighing process is guaranteed, and follow-up breeding management and livestock health are facilitated.

The application discloses a kind of cluster hunting method, system and execution device, it is related to unmanned ship technical field, the method includes obtaining the observation information of hunter and the observation information of moving target;According to the observation information of hunter and the observation information of moving target, based on Apollonius circle theory, determine total occupation angle of hunting;And according to total occupation angle of hunting, judge hunting stage;According to hunting stage, the speed information of hunter and the speed information of moving target, determine optimal speed of hunting;According to optimal speed of hunting, control hunter to reach moving target and carry out hunting.The application can make intelligent body adaptively complete uniform hunting to hunting target and improve hunting success rate.

The present application belongs to the field of agricultural information technology, and particularly relates to a kind of method for evaluating the effect of farming and herding household livelihood transition based on multi-scale data fusion, which first obtains and integrates multi-source data of farming and herding household scale and landscape scale; subsequently, at the scale of farming and herding household, the income-asset regression model and latent variable cluster analysis are used to generate the classification results of livelihood strategies, and the multi-item Logit model is used to analyze the driving factors; at the landscape scale, the model simulating land use change under different scenarios is constructed based on the driving factors, and the equivalent factor method is used to quantify the changes in ecosystem service value caused thereby; finally, at the regional scale, the changes in ecosystem service value are taken as the core ecological constraint, and the multi-objective programming model is used to generate the sustainable livelihood transition scheme with the optimal comprehensive benefits of ecology and economy. The present application breaks through the limitations of traditional single-scale static analysis, and realizes the multi-level dynamic coupling evaluation from micro-behavior to macro-effect.

The application provides a path traffic flow induction method considering the herding effect of travelers. By selecting a plurality of paths as induction paths and providing path subsidy information to part of the travelers, the part of the travelers is attracted to select the induction paths for traveling, and the rest of the travelers are guided to select the induction paths under the influence of the herding effect. Therefore, the application constructs a bi-level programming model as a traffic flow regulation model, the upper model of which takes the minimum system total travel time cost and path subsidy cost as an objective function, and the lower model of which is a dynamic evolution model considering the herding effect under the given induction paths. The model is solved by a genetic algorithm, and example analysis shows that the model can effectively reduce the system total travel time cost of the whole network and relieve traffic congestion to a certain extent. Meanwhile, the existence of the herding effect can reduce the subsidy cost while reducing the system total travel time cost of the road network, and further improve the effect of the traffic flow regulation strategy based on the path subsidy.

This invention discloses a navigation decision-making method and system for a quadruped herding robot in a wild pasture, belonging to the field of mobile robot navigation technology. First, by integrating multi-source terrain geometric features such as slope, roughness, and elevation difference, and introducing observation quality factors and directional consistency penalties, a Bayesian log-probability model is used for temporal probability updates. Then, combined with a three-level decision logic of "soft threshold - counting lag - hard constraint," a continuous passable probability is output, achieving a refined quantitative assessment of risks in complex local terrains such as potholes, steep slopes, and vegetation obstruction. Based on this, an adaptive multi-objective cost function based on situational awareness is constructed, dynamically integrating three types of situational factors: environmental uncertainty, motion risk, and proximity risk. The weights between safety and efficiency are adjusted in real time, thereby achieving an online trade-off between path length, travel time, and passage safety, ultimately generating a locally optimal navigation path for the quadruped robot in a natural grassland pasture environment.

The application discloses a sweeping robot driving and dispersing method based on a shepherd dog model, and specifically comprises the following steps: S1, initializing the sweeping robot and the driving robot; S2, the driving robot adopts a spiral motion mode to drive and disperse the sweeping robot, and a first dispersion result is obtained; S3, a sweeping area grid is constructed, and the number of sweeping robots of each grid is calculated according to the first dispersion result, and a density matrix is obtained; S4, the density maximum area and the density minimum area are obtained according to the density matrix, and then the driving robot drives the sweeping robots in the density maximum area to the density minimum area.