115 skills found · Page 1 of 4
bulletphysics / Bullet3Bullet Physics SDK: real-time collision detection and multi-physics simulation for VR, games, visual effects, robotics, machine learning etc.
angeluriot / Galaxy SimulationAn n-body type simulation using GPU acceleration to simulate galaxies, galaxy collisions and expanding universes.
balrifaee / Net MPC Collision AvoidanceMATLAB Simulation of Networked Model Predictive Control for Vehicle Collision Avoidance
patriciogonzalezvivo / OfxFluidGPU Fluid Simulation with a collisions layer
SHITIANYU-hue / Efficient Motion PlanningTo guarantee safe and efficient driving for automated vehicles in complicated traffic conditions, the motion planning module of automated vehicles are expected to generate collision-free driving policies as soon as possible in varying traffic environment. However, there always exist a tradeoff between efficiency and accuracy for the motion planning algorithms. Besides, most motion planning methods cannot find the desired trajectory under extreme scenarios (e.g., lane change in crowded traffic scenarios). This study proposed an efficient motion planning strategy for automated lane change based on Mixed-Integer Quadratic Optimization (MIQP) and Neural Networks. We modeled the lane change task as a mixed-integer quadratic optimization problem with logical constraints, which allows the planning module to generate feasible, safe and comfortable driving actions for lane changing process. Then, a hierarchical machine learning structure that consists of SVM-based classification layer and NN-based action learning layer is established to generate desired driving policies that can make online, fast and generalized motion planning. Our model is validated in crowded lane change scenarios through numerical simulations and results indicate that our model can provide optimal and efficient motion planning for automated vehicles
kashimAstro / OfxClothcloth simulation with collision
Abeilles14 / Velocity Obstacle And Motion PlanningA Collision Avoidance and Path Planning Framework implemented for a dual arm Pick and Place robot task simulation. Velocity Obstacles and RRTStar Motion Planner are used in the algorithm to plan dynamic collisionless trajectories.
donkozoltan / EduPICeduPIC is an introductory, particle-based code for radio-frequency plasma simulation that utilizes the Particle-In-Cell simulation approach combined with the Monte Carlo treatment of collision processes (PIC/MCC)
kotlin-graphics / BulletJVM Bullet Physics SDK: real-time collision detection and multi-physics simulation for VR, games, visual effects, robotics, machine learning etc.
iamyoukou / Sdf2dWithMPM2DSDF-based collision detection with MPM-based simulation
palmerabollo / Rvo2 JsReciprocal Collision Avoidance for Real-Time Multi-Agent Simulation (port to Javascript). This is an alpha release of a RVO2 port from the C# version to Javascript, only for research purposes.
yangliu28 / Two Scara CollaborationSimulation of collaboration of two SCARA robots with collision avoidance.
XuShenLZ / DataMPC ParkingarXiv 2011.00413: (MATLAB Simulation) Collision Avoidance in Tightly-Constrained Environments without Coordination: a Hierarchical Control Approach.
caoty777 / Simulated Multi Robot Arm Object Passing SystemFinal project for 'ECE470: Intro to Robotics' at UIUC. Python code+API to create a robot simulation in Vrep software. Robot arm forward/inverse kinematics, automation system design, path planning (collision avoidance)
tianxiao / Recent Advances In Real Time Collision And Proximity Computations For Games And Simulations Recent Advances in Real-Time Collision and Proximity Computations for Games and Simulations
Mingtzge / MiVeCC With DRLThis is a Multi-intersection Vehicular Cooperative Control (MiVeCC) scheme to enable cooperation among vehicles in a 3*3 unsignalized intersections. we proposed a algorithm combined heuristic-rule and two-stage deep reinforcement learning. The heuristic-rule achieves vehicles across the intersections without collisions. Based on the heuristic-rule, DDPG is used to optimize the collaborative control of vehicles and improve the traffic efficiency. Simulation results show that the proposed algorithm can improve travel efficiency at multiple intersections by up to 4.59 times without collision compared with existing methods.
koesan / ORCUSAutonomous swarm kamikaze drone system for area surveillance and target engagement. Features AI-based target detection, Pixel-to-GPS localization, coordinated swarm task allocation, and collision-safe parallel operations. Built on ArduPilot SITL, ROS, and Gazebo simulation.
kliment / SimarrangeSTL 2D plate packer with collision simulation
nobuyuki83 / Cloth Sim Self Collisioncloth simulation with self-collision
Michelle-NYX / Traffic Simulator Q LearningWe propose a driver modeling process and its evaluation results of an intelligent autonomous driving policy, which is obtained through reinforcement learning techniques. Assuming a MDP decision making model, Q-learning method is applied to simple but descriptive state and action spaces, so that a policy is developed within limited computational load. The driver could perform reasonable maneuvers, like acceleration, deceleration or lane-changes, under usual traffic conditions on a multi-lane highway. A traffic simulator is also construed to evaluate a given policy in terms of collision rate, average travelling speed, and lane change times. Results show the policy gets well trained under reasonable time periods, where the driver acts interactively in the stochastic traffic environment, demonstrating low collision rate and obtaining higher travelling speed than the average of the environment. Sample traffic simulation videos are postedsit on YouTube.
