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Robotics
Adaptive Road Following using Self-Supervised Learning and Reverse Optical Flow
DP-SLAM: Fast, Robust Simultaneous Localization and Mapping Without Predetermined Landmarks
The Dynamic Window Approach to Collision Avoidance
Online Trajectory Generation: Basic Concepts for Instantaneous Reactions to Unforeseen Events
Probablistic Roadmaps for Path Planning in High-Dimensional Configuration Spaces
Rapidly-Exploring Random Trees: A New Tool for Path Planning
RGB-D Mapping: Using Depth Cameras for Dense 3D Modeling of Indoor Environments
Reasoning for the new papers:
The dynamic window approach to collision avoidance is an influential paper for mobile robots. The method is based on a robot's dynamics rather than higher-level representations of a robot and/or obstacles in an environment.
The PRM and RRT algorithms are two seminal papers in robot motion planning. The problem of motion planning scales exponentially with the degrees of freedom a robot has and the degrees of freedom the obstacles in an environment have. Thus, planning with high degrees of freedom leads to many problems such as incompleteness and extremely slow speed. The PRM method was the first to propose a sampling-based stratey to deal with motion planning and created a practical method for offline planning of robot manipulators. The RRT method modified PRM by using a tree structure rather than a graph so that non-holonomic and other constraints could be considered when planning.
The Instantaneous Trajectory Generation method is relatively new, but very important. It allows for extremely fast trajectory generation for robots of high degrees of freedom (motion states generated within 1 millisecond). It has been used to implement robot sword fighting and other activities that require fast reaction-based planning. The author started a business based simply on the work and has shown the algorithm's success in many robot applications.