446 research outputs found
Supervised Autonomous Locomotion and Manipulation for Disaster Response with a Centaur-like Robot
Mobile manipulation tasks are one of the key challenges in the field of
search and rescue (SAR) robotics requiring robots with flexible locomotion and
manipulation abilities. Since the tasks are mostly unknown in advance, the
robot has to adapt to a wide variety of terrains and workspaces during a
mission. The centaur-like robot Centauro has a hybrid legged-wheeled base and
an anthropomorphic upper body to carry out complex tasks in environments too
dangerous for humans. Due to its high number of degrees of freedom, controlling
the robot with direct teleoperation approaches is challenging and exhausting.
Supervised autonomy approaches are promising to increase quality and speed of
control while keeping the flexibility to solve unknown tasks. We developed a
set of operator assistance functionalities with different levels of autonomy to
control the robot for challenging locomotion and manipulation tasks. The
integrated system was evaluated in disaster response scenarios and showed
promising performance.Comment: In Proceedings of IEEE/RSJ International Conference on Intelligent
Robots and Systems (IROS), Madrid, Spain, October 201
Overcoming barriers and increasing independence: service robots for elderly and disabled people
This paper discusses the potential for service robots to overcome barriers and increase independence of
elderly and disabled people. It includes a brief overview of the existing uses of service robots by disabled and elderly
people and advances in technology which will make new uses possible and provides suggestions for some of these new
applications. The paper also considers the design and other conditions to be met for user acceptance. It also discusses
the complementarity of assistive service robots and personal assistance and considers the types of applications and
users for which service robots are and are not suitable
An overview of robotics and autonomous systems for harsh environments
Across a wide range of industries and applications, robotics and autonomous systems can fulfil the crucial and challenging tasks such as inspection, exploration, monitoring, drilling, sampling and mapping in areas of scientific discovery, disaster prevention, human rescue and infrastructure management, etc. However, in many situations, the associated environment is either too dangerous or inaccessible to humans. Hence, a wide range of robots have been developed and deployed to replace or aid humans in these activities. A look at these harsh environment applications of robotics demonstrate the diversity of technologies developed. This paper reviews some key application areas of robotics that involve interactions with harsh environments (such as search and rescue, space exploration, and deep-sea operations), gives an overview of the developed technologies and provides a discussion of the key trends and future directions common to many of these areas
Terrain Classification from Body-mounted Cameras during Human Locomotion
Abstract—This paper presents a novel algorithm for terrain type classification based on monocular video captured from the viewpoint of human locomotion. A texture-based algorithm is developed to classify the path ahead into multiple groups that can be used to support terrain classification. Gait is taken into account in two ways. Firstly, for key frame selection, when regions with homogeneous texture characteristics are updated, the fre-quency variations of the textured surface are analysed and used to adaptively define filter coefficients. Secondly, it is incorporated in the parameter estimation process where probabilities of path consistency are employed to improve terrain-type estimation. When tested with multiple classes that directly affect mobility a hard surface, a soft surface and an unwalkable area- our proposed method outperforms existing methods by up to 16%, and also provides improved robustness. Index Terms—texture, classification, recursive filter, terrain classification I
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
An Architecture for Online Affordance-based Perception and Whole-body Planning
The DARPA Robotics Challenge Trials held in December 2013 provided a landmark demonstration of dexterous mobile robots executing a variety of tasks aided by a remote human operator using only data from the robot's sensor suite transmitted over a constrained, field-realistic communications link. We describe the design considerations, architecture, implementation and performance of the software that Team MIT developed to command and control an Atlas humanoid robot. Our design emphasized human interaction with an efficient motion planner, where operators expressed desired robot actions in terms of affordances fit using perception and manipulated in a custom user interface. We highlight several important lessons we learned while developing our system on a highly compressed schedule
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