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484
Recent progress in local and global traversability for planetary rovers
- IN IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION
, 2000
"... Autonomous planetary rovers operating in vast unknown environments must operate efficiently because of size, power and computing limitations. Recently, we have developed a rover capable of efficient obstacle avoidance and path planning. The rover uses binocular stereo vision to sense potentially clu ..."
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Cited by 73 (12 self)
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Autonomous planetary rovers operating in vast unknown environments must operate efficiently because of size, power and computing limitations. Recently, we have developed a rover capable of efficient obstacle avoidance and path planning. The rover uses binocular stereo vision to sense potentially cluttered outdoor environments. Navigation is performed by a combination of several modules that each ÒvoteÓ for the next best action for the robot to execute. The key distinction of our system is that it produces globally intelligent behavior with a small computational resourceÑ all processing and decision making is done on a single processor. These algorithms have been tested on our prototype rover, Bullwinkle, outdoors and have recently driven the rover 100 m at speeds of 15 cm/ sec. In this paper we report on the extensions on the systems that we have previously developed that were necessary to achieve autonomous navigation in this domain.
Real-Time Map Building and Navigation for Autonomous Robots in Unknown Environments
- IEEE Transactions on Systems, Man, and Cybernetics
, 1999
"... An algorithmic solution method is presented for the problem of autonomous robot motion in completely unknown environments. Our approach is based on the alternate execution of two fundamental processes: map building and navigation. In the former, range measures are collected through the robot exteroc ..."
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Cited by 68 (4 self)
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An algorithmic solution method is presented for the problem of autonomous robot motion in completely unknown environments. Our approach is based on the alternate execution of two fundamental processes: map building and navigation. In the former, range measures are collected through the robot exteroceptive sensors and processed in order to build a local representation of the surrounding area. This representation is then integrated in the global map so far reconstructed by filtering out insufficient or conflicting information. In the navigation phase, an A*-based planner generates a local path from the current robot position to the goal. Such path is safe inside the explored area and provides a direction for further exploration. The robot follows the path up to the boundary of the explored area, terminating its motion if unexpected obstacles are encountered. The most peculiar aspects of our method are the use of fuzzy logic for efficiently building and modifying the environment map, and ...
Issues in multi-robot coalition formation
- IN PROC. MULTI-ROBOT SYST. FROM SWARMS TO INTELL. AUTOMATA
, 2006
"... As the community strives towards autonomous multirobot systems, there is a need for these systems to autonomously form coalitions to complete assigned missions. Numerous coalition formation algorithms have been proposed in the software agent literature. Algorithms exist that form agent coalitions in ..."
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Cited by 66 (4 self)
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As the community strives towards autonomous multirobot systems, there is a need for these systems to autonomously form coalitions to complete assigned missions. Numerous coalition formation algorithms have been proposed in the software agent literature. Algorithms exist that form agent coalitions in both super additive and non-super additive environments. The algorithmic techniques vary from negotiation-based protocols in multi-agent system (MAS) environments to those based on computation in distributed problem solving (DPS) environments. Coalition formation behaviors have also been discussed in relation to game theory. Despite the plethora of MAS coalition formation literature, to the best of our knowledge none of the proposed algorithms have been demonstrated with an actual multi-robot system. There exists a discrepancy between the multi-agent algorithms and their applicability to the multi-robot domain. This paper aims to bridge that discrepancy by unearthing the issues that arise while attempting to tailor these algorithms to the multi-robot domain. A well-known multi-agent coalition formation algorithm has been studied in order to identify the necessary modifications to facilitate its application to the multi-robot domain. This paper reports multi-robot coalition formation results based upon simulation and actual robot experiments. A multi-agent coalition formation algorithm has been demonstrated on an actual robot system.
Reciprocal n-body Collision Avoidance
- INTERNATIONAL SYMPOSIUM ON ROBOTICS RESEARCH
, 2009
"... In this paper, we present a formal approach to reciprocal n-body collision avoidance, where multiple mobile robots need to avoid collisions with each other while moving in a common workspace. In our formulation, each robot acts fully independently, and does not communicate with other robots. Based o ..."
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Cited by 65 (22 self)
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In this paper, we present a formal approach to reciprocal n-body collision avoidance, where multiple mobile robots need to avoid collisions with each other while moving in a common workspace. In our formulation, each robot acts fully independently, and does not communicate with other robots. Based on the definition of velocity obstacles, we derive sufficient conditions for collision-free motion by reducing the problem to solving a low-dimensional linear program. We test our approach on several dense and complex simulation scenarios involving thousands of robots and compute collision-free actions for all of them in only a few milliseconds. To the best of our knowledge, this method is the first that can guarantee local collision-free motion for a large number of robots in a cluttered workspace.
An Affective Mobile Robot Educator with a Full-time Job
, 1999
"... Sage is a robot that has been installed at the Carnegie Museum of Natural History as a full-time autonomous member of the staff. Its goal is to provide educational content to museum visitors in order to augment their museum experience. This paper discusses all aspects of the related research and ..."
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Cited by 63 (5 self)
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Sage is a robot that has been installed at the Carnegie Museum of Natural History as a full-time autonomous member of the staff. Its goal is to provide educational content to museum visitors in order to augment their museum experience. This paper discusses all aspects of the related research and development. The functional obstacle avoidance system, which departs from the conventional occupancy grid-based approaches, is described. Sage's topological navigation system, using only color vision and odometric information, is also described. Long-term statistics provide a quantitative measure of performance over a nine month trial period. The process by which Sage's educational content and personality were created and evaluated in collaboration with the museum's Divisions of Education and Exhibits is explained. Finally, the ability of Sage to conduct automatic long-term parameter adjustment is presented. 1 Introduction Dinosaur Hall (Figure 1) is the most popular exhibit at the ...
Online self-calibration for mobile robots
- in IEEE International Conference on Robotics and Automation (ICRA
, 1999
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Learning Occupancy Grid Maps With Forward Sensor Models
"... This article describes a new algorithm for acquiring occupancy grid maps with mobile robots. Existing occupancy grid mapping algorithms decompose the high-dimensional mapping problem into a collection of one-dimensional problems, where the occupancy of each grid cell is estimated independently. Thi ..."
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Cited by 59 (0 self)
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This article describes a new algorithm for acquiring occupancy grid maps with mobile robots. Existing occupancy grid mapping algorithms decompose the high-dimensional mapping problem into a collection of one-dimensional problems, where the occupancy of each grid cell is estimated independently. This induces conflicts that may lead to inconsistent maps, even for noise-free sensors. This article shows how to solve the mapping problem in the original, high-dimensional space, thereby maintaining all dependencies between neighboring cells. As a result, maps generated by our approach are often more accurate than those generated using traditional techniques. Our approach relies on a statistical formulation of the mapping problem using forward models. It employs the expectation maximization algorithm for searching maps that maximize the likelihood of the sensor measurements.
An Integrated Approach to Goal-directed Obstacle Avoidance under Dynamic Constraints for Dynamic Environments
- IN IEEE-RSJ INT. CONF. ON INTELLIGENT ROBOTS AND SYSTEMS
, 2002
"... Whenever robots are installed in populated environments, they need appropriate techniques to avoid collisions with unexpected obstacles. Over the past years several reactive techniques have been developed that use heuristic evaluation functions to choose appropriate actions whenever a robot encounte ..."
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Cited by 59 (7 self)
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Whenever robots are installed in populated environments, they need appropriate techniques to avoid collisions with unexpected obstacles. Over the past years several reactive techniques have been developed that use heuristic evaluation functions to choose appropriate actions whenever a robot encounters an unforeseen obstacle. Whereas the majority of these approaches determines only the next steering command, some additionally consider sequences of possible poses. However, they generally do not consider sequences of actions in the velocity space. Accordingly, these methods are not able to slow down the robot early enough before it has to enter a narrow passage. In this paper we present a new approach that integrates path planning with sensor-based collision avoidance. Our algorithm simultaneously considers the robot's pose and velocities during the planning process. We employ different strategies to deal with the huge state space that has to be explored. Our method has been implemented and tested on real robots and in simulation runs. Extensive experiments demonstrate that our technique can reliably control mobile robots moving at high speeds.
A state-of-the-art 3D sensor for robot navigation
- In IEEE/RSJ Int. Conf. on Intelligent Robots and Systems
, 2004
"... Abslracl-This paper relates first experiences using a stateof-the.art, time-of-flight sensor that is able to deliver 3D images. The properties and capabilities of the Sensor make it a potential powerful tool for applications within mobile robotics especially for real-time tasks, as the sensor featum ..."
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Cited by 52 (1 self)
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Abslracl-This paper relates first experiences using a stateof-the.art, time-of-flight sensor that is able to deliver 3D images. The properties and capabilities of the Sensor make it a potential powerful tool for applications within mobile robotics especially for real-time tasks, as the sensor featum B frame rate of up 1 30 fames per second. Ils capabilities in terms of basic obstacle avoidance and local path-planning am eralualed and compared to the performance of a shndard laser sEmner. I.
The Lane-Curvature Method for Local Obstacle Avoidance
, 1998
"... The Lane-Curvature Method (LCM) presented in this paper is a new local obstacle avoidance method for indoor mobile robots. The method combines the Curvature-Velocity Method (CVM) with a new directional method called the Lane Method. The lane method divides the environment into lanes, and then choose ..."
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Cited by 44 (6 self)
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The Lane-Curvature Method (LCM) presented in this paper is a new local obstacle avoidance method for indoor mobile robots. The method combines the Curvature-Velocity Method (CVM) with a new directional method called the Lane Method. The lane method divides the environment into lanes, and then chooses the best lane to follow to optimize travel along a desired heading. A local heading is then calculated for entering and following the best lane, and CVM uses this heading to determine the optimal translational and rotational velocities, considering the heading direction, physical limitations, and environmental constraints. By combining both directional and velocity space methods, LCM yields safe collision-free motion as well as smooth motion taking the dynamics of the robot into account. Introduction A local obstacle avoidance method for indoor mobile robots in unknown or partially known environments is investigated. The method should guide a robot through a collision free space along a g...
