According to an example aspect of the present invention, there is provided a method including the steps of: assigning a set of obstacle analysis parameters for a mining vehicle, wherein the set of obstacle analysis parameters is specific to a portion of the mining vehicle; detecting, by an obstacle detection function of the mining vehicle, an obstacle candidate on the basis of processing scanning data from a scanner of the mining vehicle; performing an obstacle analysis on the basis of a determined size of the obstacle candidate and the set of obstacle analysis parameters assigned for the mining vehicle to classify the obstacle candidate and determine if the obstacle candidate is an obstacle to be avoided, and providing, in response to the obstacle analysis indicating that the obstacle candidate is an obstacle to be avoided, an alarm or control signal to avoid the mining vehicle hitting the obstacle.

A robot comprises an auger-based drive system, a memory, and a processor coupled with the memory and configured to control movement of the robot via the auger-based drive system. The processor obtains a first measurement of an angle of slope of a portion of piled granular material in a bulk store. In response to the first measurement satisfying a first condition, the robot traverses the portion of piled granular material to incite sediment gravity flow in the portion of piled granular material by disruption of viscosity of the portion of piled granular material through agitation of the portion of piled granular material by auger rotation of the auger-based drive system. The processor obtains a second measurement of the angle of slope of the portion of piled granular material. In response to the second measurement satisfying a second condition, the robot ceases traversal of the portion of piled granular material.

A method for inverting driving instructions of a working machine includes a first step of entering and initiating a driving instruction. In a second step, position data of the working machine are associated with the driving instruction. In a third step, a cancellation of the driving instruction is entered and the driving instruction is terminated. In a fourth step, position data of the working machine are associated with the cancellation of the driving instruction. With reference to the associated position data a corridor for the driving instruction is defined, and in a fifth step the driving instruction is inverted in such manner that the driving instruction is initiated and cancelled in the reverse sequence when the working machine travels along the corridor in the reverse direction.

A slope management system and associated method for equipment may control the equipment by preventing operation of the equipment if an actual angle of the equipment relative to level is outside of a slope limit for the equipment. Such equipment includes at least one of an aerial device, a dump truck, a crane, a personnel lift, a digger derrick, a tele-handler, a scissor lift, a forklift, a bucket truck, a wood chipper, a brush chipper, a vacuum truck, a directional drill, a bull dozer, a backhoe, a wheeled loader, a tracked loader, a skid steer, a compact track loader, an excavator, a compactor, a steam roller, a motor grader, a chip truck, a tractor, combinations thereof, and/or as otherwise desired.

Embodiments presented provide for an apparatus used for wellbore intervention, evaluation and stimulation. The apparatus provides a tractor mechanism, a power supply, tools and sensors used in evaluation and stimulation activities with hydrocarbon recovery operations.

One method for finishing a surface includes utilizing a hovering surface finisher with a plurality of attachments and finishers coupled thereto. The surface finisher images a grid on an unfinished surface via a camera and a GPS tracks the location of the surface relative to the surface finisher. A user may program specified parameters, including height and angle above the surface, and speed and time at which the surface finisher flies across the grid to finish the surface. The system operating this process may include a connector that attaches the finisher to the surface finisher and sensors for determining the locational parameters. Utilizing the precise locational information from the sensors, the surface finisher may create various textures on the surface that increase the surface's longevity and safety by reducing slip and fall injuries.

A robot comprises an auger-based drive system, a memory, and a processor coupled with the memory and configured to control movement of the robot, via the auger-based drive system, relative to grain in a grain bin. The processor is further configured to direct traversal, by the robot, of a landing zone portion of a surface of a pile of the grain during load-in of the grain to disperse broken grain and foreign material away from the landing zone portion. The landing zone portion is located in a center of the grain bin where the grain lands as it is augured into the grain bin during load-in. The dispersal is affected in part by rotation of augers of the auger-based drive system.

An unmanned vehicle includes: a travel device; an obstacle sensor; a host path storage unit that stores a host path; a travel control unit that controls the travel device based on the host path; an oncoming path storage unit that stores an oncoming path to be given to an oncoming vehicle; and an obstacle presence/absence determination unit that determines whether or not an obstacle is located on the oncoming path based on detection data from the obstacle sensor.

A modular micro-factory swarm for autonomous urban construction is disclosed. Each unit is a self-assembling robotic tile that (i) 3D-prints structural elements from locally characterized feedstock, (ii) powers itself via a dual renewable system (deployable photovoltaic array and hydrogen electrolysis/fuel-cell), and (iii) communicates over a mesh network for coordinated tasking. A cost-based planner assigns paths and jobs to minimize energy, time, and terrain risk. After each extrusion, the tile runs on-board structural checks (ultrasonic echo and vibrational resonance) and records pass/fail metrics. Build provenance is bound cryptographically: a hardware security module signs a build object identifier that hashes tile ID, task node, material signature, time, and location; signed records are committed to a distributed ledger. Actuation is gated by location-specific consent tokens verified against policy maps before printing proceeds. The architecture enables peer-to-peer orchestration, verifiable quality control, and closed-loop energy autonomy, reducing reliance on infrastructure and supervision.

The present invention relates to the technical field of path planning, and provides a deep reinforcement learning-based path exploration parameter optimization system. The system comprises: a variable parameter path planning module, configured to perform node exploration based on a deep reinforcement learning network, conduct collision detection on child nodes in a child node set, calculate cost values for all child nodes, and finally generate a loading and parking path using a Reeds-Shepp curve; an environmental state space modeling module, configured to perform regional division of obstacles around a current node and conduct environmental state space modeling; and a deep learning parameter optimization module, configured to construct a deep learning network to compute an optimal step size and an optimal steering angle, build a reward function to optimize the deep learning network, and simultaneously execute a training process of the deep learning network.