Contextualized Robot Navigation

In order to improve the interaction between humans and robots, robots need to be able to move about in a way that is appropriate to the complex environments around them. One way to investigate how the robots should move is through the lens of theatre, which provides us with ways to analyze the robot\u27s movements and the motivations for moving in particular ways. In particular, this has proven useful for improving robot navigation. By altering the costmaps used for path planning, robots can navigate around their environment in ways that incorporate additional contexts. Experimental results with user studies have shown altered costmaps to have a significant effect on the interaction, although the costmaps must be carefully tuned to get the desired effect. The new layered costmap algorithm builds on the established open-source navigation platform, creating a robust system that can be extended to handle a wide range of contextual situations

Integration of ROS navigation stack with dynamic environment information in gazebo simulation

Sensing the environment is a crucial task that robots have to perform to navigate autonomously. Furthermore, it must be well executed to make navigation safer and collision- free. As autonomous mobile robots are being deployed in several applications, they often encounter dynamic habitats, where sensing and perceiving the environment becomes harder. This work proposes integrating a wireless sensor network with the Robotic Operating System to incorporate data into layered costmaps used by the robot to navigate, feeding the algorithms with advanced information about the territory. The architecture was tested in simulation, where we could validate the structure and collect data showing improved paths calculated and reduced computational load through better parametrization. Thus, this strategy ensures that the advanced information about the environment has improved the navigation process.The authors are grateful to the Research Centre in Digitalization and Intelligent Robotics (CeDRI) for sharing its facilities and material, and also to the Foundation for Science and Technology (FCT, Portugal) for financial support as mentioned earlier.info:eu-repo/semantics/publishedVersio

Real-Time Navigation for Bipedal Robots in Dynamic Environments

The popularity of mobile robots has been steadily growing, with these robots being increasingly utilized to execute tasks previously completed by human workers. For bipedal robots to see this same success, robust autonomous navigation systems need to be developed that can execute in real-time and respond to dynamic environments. These systems can be divided into three stages: perception, planning, and control. A holistic navigation framework for bipedal robots must successfully integrate all three components of the autonomous navigation problem to enable robust real-world navigation. In this paper, we present a real-time navigation framework for bipedal robots in dynamic environments. The proposed system addresses all components of the navigation problem: We introduce a depth-based perception system for obstacle detection, mapping, and localization. A two-stage planner is developed to generate collision-free trajectories robust to unknown and dynamic environments. And execute trajectories on the Digit bipedal robot's walking gait controller. The navigation framework is validated through a series of simulation and hardware experiments that contain unknown environments and dynamic obstacles.Comment: Submitted to 2023 IEEE International Conference on Robotics and Automation (ICRA). For associated experiment recordings see https://www.youtube.com/watch?v=WzHejHx-Kz

Autonomous navigation for mobility scooters: a complete framework based on open-source software

In recent years, there has been a growing demand for small vehicles targeted at users with mobility restrictions and designed to operate on pedestrian areas. The users of these vehicles are generally required to be in control for the entire duration of their journey, but a lot more people could benefit from them if some of the driving tasks could be automated. In this scenario, we set out to develop an autonomous mobility scooter, with the aim to understand the commercial feasibility of a similar product. This paper reports on the progress of this project, proposing a framework for autonomous navigation on pedestrian areas, and focusing in particular on the construction of suitable costmaps. The proposed framework is based on open-source software, including a library created by the authors for the generation of costmaps

Incorporating Perception Uncertainty in Human-Aware Navigation: A Comparative Study

In this work, we present a novel approach to human-aware navigation by probabilistically modelling the uncertainty of perception for a social robotic system and investigating its effect on the overall social navigation performance. The model of the social costmap around a person has been extended to consider this new uncertainty factor, which has been widely neglected despite playing an important role in situations with noisy perception. A social path planner based on the fast marching method has been augmented to account for the uncertainty in the positions of people. The effectiveness of the proposed approach has been tested in extensive experiments carried out with real robots and in simulation. Real experiments have been conducted, given noisy perception, in the presence of single/multiple, static/dynamic humans. Results show how this approach has been able to achieve trajectories that are able to keep a more appropriate social distance to the people, compared to those of the basic navigation approach, and the human-aware navigation approach which relies solely on perfect perception, when the complexity of the environment increases. Accounting for uncertainty of perception is shown to result in smoother trajectories with lower jerk that are more natural from the point of view of humans

Human-aware navigation for autonomous mobile robots for intra-factory logistics

This paper presents a human-aware navigation system for mobile robots targeted to cooperative assembly in intra-factory logistics scenarios. To improve overall efficiency of the operator-robot ensemble, assembly stations and operators are modelled as cost functions in a layered cost map supporting the robot navigation system. At each new sensory update, the system uses each operator’s estimated location to affect the cost map accordingly. To promote predictability and comfort in the human operator, the cost map is affected according to the Proxemics theory, properly adapted to take into account the layout activity space of the station in which the operator is working. Knowledge regarding which task and station are being handled by the operator are assumed to be given to the robot by the factory’s computational infrastructure. To foster integration in existing robots, the system is implemented on top of the navigation system of the Robot Operating System (ROS).info:eu-repo/semantics/acceptedVersio

On-Board Human-Aware Navigation for Indoor Resource-Constrained Robots: A Case-Study with the Ranger

Introducing simple robotic platforms into domes- tic environments is faced with the challenge of social accept- ability. Therefore human-aware navigation is a must for robots operating in environments shared with human users. In this work, we focus on the human-aware navigation problem in a structured environment for a robot with limited sensing and constrained maneuvering called Ranger. The Ranger is a simple domestic robotic platform designed for interacting with children. The system combines person detection and tracking —which is the result of fusing laser-scan and depth-image based detectors provided by an RGB-D camera—, basic autonomous navigation and the concept of personal space. We rely only on the on-board sensors for mapping, localization, human tracking, and navigation. Systematic experiments are carried out with a real robot in the presence of a human in order to compare our human-aware navigation with a non human-aware simple approach. The results show that human-aware navigation is able to achieve trajectories which are respecting the personal spaces of the human and are thus more acceptable for the users