Jamie Snape

The Hybrid Reciprocal Velocity Obstacle

We present the hybrid reciprocal velocity obstacle for collision-free and oscillation-free navigation of multiple mobile robots or virtual agents. Each robot senses its surroundings and acts independently without central coordination or communication with other robots. Our approach uses both the current position and the velocity of other robots to compute their future trajectories in order to avoid collisions. Moreover, our approach is reciprocal and avoids oscillations by explicitly taking into account that the other robots sense their surroundings as well and change their trajectories accordingly. We apply hybrid reciprocal velocity obstacles to iRobot Create mobile robots and demonstrate direct, collision-free, and oscillation-free navigation.

Reciprocal collision avoidance with acceleration-velocity obstacles

We present an approach for collision avoidance for mobile robots that takes into account acceleration constraints. We discuss both the case of navigating a single robot among moving obstacles, and the case of multiple robots reciprocally avoiding collisions with each other while navigating a common workspace. Inspired by the concept of velocity obstacles [3], we introduce the acceleration-velocity obstacle (AVO) to let a robot avoid collisions with moving obstacles while obeying acceleration constraints. AVO characterizes the set of new velocities the robot can safely reach and adopt using proportional control of the acceleration. We extend this concept to reciprocal collision avoidance for multi-robot settings, by letting each robot take half of the responsibility of avoiding pairwise collisions. Our formulation guarantees collision-free navigation even as the robots act independently and simultaneously, without coordination. Our approach is designed for holonomic robots, but can also be applied to kinematically constrained non-holonomic robots such as cars. We have implemented our approach, and we show simulation results in challenging environments with large numbers of robots and obstacles.

Independent navigation of multiple mobile robots with hybrid reciprocal velocity obstacles

We present an approach for smooth and collision-free navigation of multiple mobile robots amongst each other. Each robot senses its surroundings and acts independently without central coordination or communication with other robots. Our approach uses both the current position and the velocity of other robots to predict their future trajectory in order to avoid collisions. Moreover, our approach is reciprocal and avoids oscillations by explicitly taking into account that the other robots also sense their surroundings and change their trajectories accordingly. We build on prior work related to velocity obstacles and reciprocal velocity obstacles and introduce the concept of hybrid reciprocal velocity obstacles for collision avoidance that takes into account the kinematics of the robots and uncertainty in sensor data. We apply our approach to a set of iRobot Create robots using centralized sensing and show natural, direct, and collision-free navigation in several challenging scenarios.

Smooth and collision-free navigation for multiple robots under differential-drive constraints

We present a method for smooth and collision-free navigation for multiple independent robots under differential-drive constraints. Our algorithm is based on the optimal reciprocal collision avoidance formulation and guarantees both smoothness in the trajectories of the robots and locally collision-free paths. We provide proofs of these guarantees and demonstrate the effectiveness of our method in experimental scenarios using iRobot Create mobile robots navigating amongst each other.

Navigating multiple simple-airplanes in 3D workspace

We present an algorithm for collision-free navigation of multiple flying robots in three-dimensional workspace. Our approach extends the model of a simple car to a simple-airplane, which has constraints on speed and steering angle and includes a configuration variable for the altitude. We use a locally optimal reciprocal collision avoidance scheme that computes the trajectory without any collisions or oscillations for each airplane independently. In addition, our algorithm explicitly considers the kinematic and dynamic constraints of a simple-airplane and uses the notion of variable reciprocity when choosing velocities to ensure that simple-airplanes that are less constrained take more responsibility for avoiding collisions. We test our approach in two simulations and compute collision-free and oscillation-free trajectories that satisfy the kinematic and dynamic constraints of each simple-airplane.

Smooth Coordination and Navigation for Multiple Differential-Drive Robots

Multiple independent robots sharing the workspace need to be able to navigate to their goals while avoiding collisions with each other. In this paper, we describe and evaluate two algorithms for smooth and collision-free navigation for multiple independent differential-drive robots.We extend reciprocal collision avoidance algorithms based on velocity obstacles and on acceleration-velocity obstacles. We implement bothmethods on multiple iRobot Create differential-drive robots, and report on the quality and ability of the robots using the two algorithms to navigate to their goals in a smooth and collision-free manner.