Simultaneous localization and mapping (SLAM) is the computational problem of constructing or updating a map of an unknown environment while simultaneously keeping track of an agent's location within it. While this initially appears to be a chicken or the egg problem, there are several algorithms known to solve it in, at least approximately, tractable time for certain environments. Popular approximate solution methods include the particle filter, extended Kalman filter, covariance intersection, and GraphSLAM. SLAM algorithms are based on concepts in computational geometry and computer vision, and are used in robot navigation, robotic mapping and odometry for virtual reality or augmented reality.
Motion planning, also path planning is a computational problem to find a sequence of valid configurations that moves the object from the source to destination. The term is used in computational geometry, computer animation, robotics and computer games.
Direct torque control (DTC) is one method used in variable-frequency drives to control the torque of three-phase AC electric motors. This involves calculating an estimate of the motor's magnetic flux and torque based on the measured voltage and current of the motor.
Obstacle avoidance, in robotics, is a critical aspect of autonomous navigation and control systems. It is the capability of a robot or an autonomous system/machine to detect and circumvent obstacles in its path to reach a predefined destination. This technology plays a pivotal role in various fields, including industrial automation, self-driving cars, drones, and even space exploration. Obstacle avoidance enables robots to operate safely and efficiently in dynamic and complex environments, reducing the risk of collisions and damage.
A rapidly exploring random tree (RRT) is an algorithm designed to efficiently search nonconvex, high-dimensional spaces by randomly building a space-filling tree. The tree is constructed incrementally from samples drawn randomly from the search space and is inherently biased to grow towards large unsearched areas of the problem. RRTs were developed by Steven M. LaValle and James J. Kuffner Jr. They easily handle problems with obstacles and differential constraints and have been widely used in autonomous robotic motion planning.
Robot localization denotes the robot's ability to establish its own position and orientation within the frame of reference. Path planning is effectively an extension of localisation, in that it requires the determination of the robot's current position and a position of a goal location, both within the same frame of reference or coordinates. Map building can be in the shape of a metric map or any notation describing locations in the robot frame of reference.
Occupancy Grid Mapping refers to a family of computer algorithms in probabilistic robotics for mobile robots which address the problem of generating maps from noisy and uncertain sensor measurement data, with the assumption that the robot pose is known. Occupancy grids were first proposed by H. Moravec and A. Elfes in 1985.
The Guidance, Control and Decision Systems Laboratory (GCDSL) is situated in the Department of Aerospace Engineering at the Indian Institute of Science in Bangalore, India. The Mobile Robotics Laboratory (MRL) is its experimental division. They are headed by Dr. Debasish Ghose, Full Professor.
Johann Borenstein is an Israeli roboticist and Professor at the University of Michigan. Borenstein is well known for his work in autonomous obstacle avoidance, and is credited with the development of the Vector Field Histogram.
The Mobile Robot Programming Toolkit (MRPT) is a cross-platform and open source C++ library aimed to help robotics researchers to design and implement algorithms related to Simultaneous Localization and Mapping (SLAM), computer vision and motion planning. Different research groups have employed MRPT to implement projects reported in some of the major robotics journals and conferences.
Allen was a robot introduced by Rodney Brooks and his team in the late 1980s, and was their first robot based on subsumption architecture. It had sonar distance and odometry on board, and used an offboard lisp machine to simulate subsumption architecture. It resembled a footstool on wheels.
In robotics and motion planning, a velocity obstacle, commonly abbreviated VO, is the set of all velocities of a robot that will result in a collision with another robot at some moment in time, assuming that the other robot maintains its current velocity. If the robot chooses a velocity inside the velocity obstacle then the two robots will eventually collide, if it chooses a velocity outside the velocity obstacle, such a collision is guaranteed not to occur.
Any-angle path planning algorithms are pathfinding algorithms that search for a Euclidean shortest path between two points on a grid map while allowing the turns in the path to have any angle. The result is a path that cuts directly through open areas and has relatively few turns. More traditional pathfinding algorithms such as A* either lack in performance or produce jagged, indirect paths.
MiroSurge is a presently prototypic robotic system designed mainly for research in minimally invasive telesurgery. In the described configuration, the system is designed according to the master slave principle and enables the operator to remotely control minimally invasive surgical instruments including force/torque feedback. The scenario is developed at the Institute of Robotics and Mechatronics within the German Aerospace Center (DLR).
Oussama Khatib is a roboticist and a professor of computer science at Stanford University, and a Fellow of the IEEE. He is credited with seminal work in areas ranging from robot motion planning and control, human-friendly robot design, to haptic interaction and human motion synthesis. His work's emphasis has been to develop theories, algorithms, and technologies, that control robot systems by using models of their physical dynamics. These dynamic models are used to derive optimal controllers for complex robots that interact with the environment in real-time.
Real-Time Path Planning is a term used in robotics that consists of motion planning methods that can adapt to real time changes in the environment. This includes everything from primitive algorithms that stop a robot when it approaches an obstacle to more complex algorithms that continuously takes in information from the surroundings and creates a plan to avoid obstacles.
Yoram Koren is an Israeli-American academic. He is the James J. Duderstadt Distinguished University Professor Emeritus of Manufacturing and the Paul G. Goebel Professor Emeritus of Engineering at the University of Michigan, Ann Arbor. Since 2014 he is a distinguished visiting professor at the Technion – Israel Institute of Technology.
The problem of Multi-Agent Pathfinding (MAPF) is an instance of multi-agent planning and consists in the computation of collision-free paths for a group of agents from their location to an assigned target. It is an optimization problem, since the aim is to find those paths that optimize a given objective function, usually defined as the number of time steps until all agents reach their goal cells. MAPF is the multi-agent generalization of the pathfinding problem, and it is closely related to the shortest path problem in the context of graph theory.
Shraga Shoval is an Israeli professor in the Department of Industrial Engineering & Management and the Dean of the Engineering Faculty at Ariel University
The wavefront expansion algorithm is a specialized potential field path planner with breadth-first search to avoid local minima. It uses a growing circle around the robot. The nearest neighbors are analyzed first and then the radius of the circle is extended to distant regions.
