Related papers: Benchmarking Metric Ground Navigation
Mobile robots are increasingly deployed in cluttered environments with movable objects, posing challenges for traditional methods that prohibit interaction. In such settings, the mobile robot must go beyond traditional obstacle avoidance,…
A major challenge to deploying robots widely is navigation in human-populated environments, commonly referred to as social robot navigation. While the field of social navigation has advanced tremendously in recent years, the fair evaluation…
Social Robot Navigation is the skill that allows robots to move efficiently in human-populated environments while ensuring safety, comfort, and trust. Unlike other areas of research, the scientific community has not yet achieved an…
Safe robot navigation is a fundamental research field for autonomous robots including ground mobile robots and flying robots. The primary objective of a safe robot navigation algorithm is to guide an autonomous robot from its initial…
Mobile robot navigation is typically regarded as a geometric problem, in which the robot's objective is to perceive the geometry of the environment in order to plan collision-free paths towards a desired goal. However, a purely geometric…
This paper presents a joint effort towards the development of a data-driven Social Robot Navigation metric to facilitate benchmarking and policy optimization for ground robots. We compiled a dataset with 4427 trajectories -- 182 real and…
Recent advancement in off-road autonomy has shown promises in deploying autonomous mobile robots in outdoor off-road environments. Encouraging results have been reported from both simulated and real-world experiments. However, unlike…
The BARN (Benchmark Autonomous Robot Navigation) Challenge took place at the 2022 IEEE International Conference on Robotics and Automation (ICRA 2022) in Philadelphia, PA. The aim of the challenge was to evaluate state-of-the-art autonomous…
The ability to autonomously navigate safely, especially within dynamic environments, is paramount for mobile robotics. In recent years, DRL approaches have shown superior performance in dynamic obstacle avoidance. However, these…
Generative navigation policies have made rapid progress in improving end-to-end learned navigation. Despite their promising results, this paradigm has two structural problems. First, the sampled trajectories exist in an abstract, unscaled…
Navigation in the real-world is hard and filled with complex scenarios. The Benchmark Autonomous Robot Navigation (BARN) Challenge is a competition that focuses on highly constrained spaces. Teams compete using a standard platform in a…
Enabling socially acceptable behavior for situated agents is a major goal of recent robotics research. Robots should not only operate safely around humans, but also abide by complex social norms. A key challenge for developing…
Robots moving safely and in a socially compliant manner in dynamic human environments is an essential benchmark for long-term robot autonomy. However, it is not feasible to learn and benchmark social navigation behaviors entirely in the…
We present Interactive Gibson Benchmark, the first comprehensive benchmark for training and evaluating Interactive Navigation: robot navigation strategies where physical interaction with objects is allowed and even encouraged to accomplish…
Mobile robots are increasingly deployed in unstructured environments where obstacles and objects are movable. Navigation in such environments is known as interactive navigation, where task completion requires not only avoiding obstacles but…
Recent protocols and metrics for training and evaluating autonomous robot navigation through crowds are inconsistent due to diversified definitions of "social behavior". This makes it difficult, if not impossible, to effectively compare…
The human-robot interaction (HRI) community has developed many methods for robots to navigate safely and socially alongside humans. However, experimental procedures to evaluate these works are usually constructed on a per-method basis. Such…
Safe visual navigation is critical for indoor mobile robots operating in cluttered environments. Existing benchmarks, however, often neglect collisions or are designed for outdoor scenarios, making them unsuitable for indoor visual…
The increasing demand for efficient last-mile delivery in smart logistics underscores the role of autonomous robots in enhancing operational efficiency and reducing costs. Traditional navigation methods, which depend on high-precision maps,…
Establishing standardized metrics for Social Robot Navigation (SRN) algorithms for assessing the quality and social compliance of robot behavior around humans is essential for SRN research. Currently, commonly used evaluation metrics lack…