Yang et al., 2025 - Google Patents
Geometry-Based Cooperative Conflict Resolution for Multi-UAV Combining Heading and Speed ControlYang et al., 2025
- Document ID
- 15786207486372938294
- Author
- Yang J
- Zhang K
- Zhong Q
- Zhang L
- Publication year
- Publication venue
- IEEE Transactions on Consumer Electronics
External Links
Snippet
A safe and efficient conflict resolution method for Autonomous Aerial Vehicles (AAVs) is essential for the safe operation of multi-AAV systems in complex environments. This paper proposes a geometry-based decentralized cooperative conflict resolution method. Firstly, the …
- 238000000034 method 0 abstract description 120
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0287—Control of position or course in two dimensions specially adapted to land vehicles involving a plurality of land vehicles, e.g. fleet or convoy travelling
- G05D1/0291—Fleet control
- G05D1/0295—Fleet control by at least one leading vehicle of the fleet
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0268—Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/0011—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot associated with a remote control arrangement
- G05D1/0027—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot associated with a remote control arrangement involving a plurality of vehicles, e.g. fleet or convoy travelling
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/0011—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot associated with a remote control arrangement
- G05D1/0044—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot associated with a remote control arrangement by providing the operator with a computer generated representation of the environment of the vehicle, e.g. virtual reality, maps
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/10—Simultaneous control of position or course in three dimensions
- G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Alonso-Mora et al. | Cooperative collision avoidance for nonholonomic robots | |
| Zhang et al. | A survey on multiple unmanned vehicles formation control and coordination: Normal and fault situations | |
| Keviczky et al. | Decentralized receding horizon control and coordination of autonomous vehicle formations | |
| Schouwenaars | Safe trajectory planning of autonomous vehicles | |
| El Ferik et al. | A Behavioral Adaptive Fuzzy controller of multi robots in a cluster space | |
| Zhao et al. | Hierarchical control framework for path planning of mobile robots in dynamic environments through global guidance and reinforcement learning | |
| Liao et al. | Model predictive control for cooperative hunting in obstacle rich and dynamic environments | |
| Jmaa et al. | A review of path planning algorithms | |
| Tutuko et al. | Route optimization of non-holonomic leader-follower control using dynamic particle swarm optimization | |
| Ceder et al. | Bird’s-eye-view trajectory planning of multiple robots using continuous deep reinforcement learning and model predictive control | |
| Hailemichael et al. | Development of a robust interval Type-2 TSK fuzzy logic controlled UAV platform | |
| Yang et al. | Geometry-Based Cooperative Conflict Resolution for Multi-UAV Combining Heading and Speed Control | |
| Mousavifard et al. | Formation control of multi-quadrotors based on deep Q-learning | |
| Mousavi et al. | On the distributed path planning of multiple autonomous vehicles under uncertainty based on model-predictive control and convex optimization | |
| Kanjanawanishkul | Coordinated path following for mobile robots using a virtual structure strategy with model predictive control | |
| Barnes | A potential field based formation control methodology for robot swarms | |
| Gao et al. | A survey on passing-through control of multi-robot systems in cluttered environments | |
| Yang et al. | C3R: A novel classification model-based coordination method for online conflict resolution of multiple unmanned aerial vehicles | |
| Wang et al. | Improved A* and fuzzy dynamic window based dynamic trajectory planning for an UAV | |
| Liao | Control, planning, and learning for multi-UAV cooperative hunting | |
| Zhao et al. | 3-D formulation of formation flight based on model predictive control with collision avoidance scheme | |
| Chand et al. | Leader-follower based control of fixed-wing multi-robot system (MRS) via split-rejoin maneuvers in 3d | |
| Hoy | Methods for collision-free navigation of multiple mobile robots in unknown cluttered environments | |
| Khachumov | Tactical level of intelligent geometric control system for unmanned aerial vehicles | |
| Roelofsen et al. | A comparative study of collision avoidance algorithms for unmanned aerial vehicles: Performance and robustness to noise |