As robots become more versatile, they are increasingly found to operate together in the same environment where they must coordinate their motion in a distributed manner. Such operation does not present problems if the...
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ISBN:
(纸本)9783642174513
As robots become more versatile, they are increasingly found to operate together in the same environment where they must coordinate their motion in a distributed manner. Such operation does not present problems if the motion is quasi-static and collisions can be easily avoided. However, when the robots follow second-order dynamics, the problem becomes challenging even for a known environment. The setup in this work considers that each robot replans its own trajectory for the next replanning cycle. The planning process must guarantee the robot's safety by ensuring collision-free paths for the considered period and by not bringing the robot to states where collisions cannot be avoided in the future. This problem can be addressed through communication among the robots, but it becomes complicated when the replanning cycles of the different robots are not synchronized and the robots make planning decisions at different time instants. This paper shows how to guarantee the safe operation of multiple communicating second-order vehicles, whose replanning cycles do not coincide, through an asynchronous, distributed motion planning framework. The method is evaluated through simulations, where each robot is simulated on a different processor and communicates with its neighbors through message passing. The simulations confirm that the approach provides safety in scenarios with up to 48 robots with second-order dynamics in environments with obstacles, where collisions occur often without a safety framework.
We present control algorithms that implement a novel planar microassembly scheme using groups of stress-engineered microrobots controlled through a single global control signal. The global control signal couples the m...
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ISBN:
(纸本)9783642003110
We present control algorithms that implement a novel planar microassembly scheme using groups of stress-engineered microrobots controlled through a single global control signal. The global control signal couples the motion of the devices, causing the system to be highly underactuated. Despite the high degree of underactuation, it is desirable that each robot be independently maneuverable. By exploiting differences in the designs and the resulting electromechanical interaction with the control signal, the behavior of the individual robots can be differentiated. We harness this differentiation by designing the control signal such that some devices remain confined in small circular orbits (limit cycles), while the non-orbiting robots perform work by making progress towards the goal. The control signal is designed to minimize the number of independent control voltage levels that are used for independent control, allowing us to maximize the number of simultaneously controllable devices. Our algorithms were tested on systems of fabricated untethered stress-engineered MEMS microrobots. The robots are 240-280 mu m x 60 mu m x 7-20 mu m in size and are controlled in parallel (simultaneously) within the same operating environment. We demonstrated the feasibility of our control algorithms by accurately assembling 5 different types of planar microstructures.
We present parallel algorithms to accelerate collision queries for sample-based motion planning. Our approach is designed for current many-core GPUs and exploits the data-parallelism and multi-threaded capabilities. I...
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ISBN:
(纸本)9783642174513
We present parallel algorithms to accelerate collision queries for sample-based motion planning. Our approach is designed for current many-core GPUs and exploits the data-parallelism and multi-threaded capabilities. In order to take advantage of high number of cores, we present a clustering scheme and collision-packet traversal to perform efficient collision queries on multiple configurations simultaneously. Furthermore, we present a hierarchical traversal scheme that performs workload balancing for high parallel efficiency. We have implemented our algorithms on commodity NVIDIA GPUs using CUDA and can perform 500,000 collision queries/second on our benchmarks, which is 10X faster than prior GPU-based techniques. Moreover, we can compute collision-free paths for rigid and articulated models in less than 100 milliseconds for many benchmarks, almost 50-100X faster than current CPU-based planners.
The possibility to jointly deploy aerial and ground robots makes sense in many application contexts of field robotics. There are indeed several cooperation schemes in which the complementarity of such heterogeneous ro...
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ISBN:
(纸本)9783642147432
The possibility to jointly deploy aerial and ground robots makes sense in many application contexts of field robotics. There are indeed several cooperation schemes in which the complementarity of such heterogeneous robots can be exploited to enhance the efficiency of autonomous robotic operations. This paper analyses the problems raised by the cooperation of ground and aerial robots. Besides the usual issues brought forth by the integration of cooperating heterogeneous autonomous systems, such systems raise particularly challenging problems for environment perception and modelling. On the basis of a review of the state of the art in the area, the paper focuses on this particular issue. It analyzes the required developments to tackle it, and sets forth some working directions.
In this paper we address the problem of trajectory planning with imperfect state information. In many real-world domains, the position of a mobile agent cannot he known perfectly;instead, the agent maintains a probabi...
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ISBN:
(纸本)9783642147432
In this paper we address the problem of trajectory planning with imperfect state information. In many real-world domains, the position of a mobile agent cannot he known perfectly;instead, the agent maintains a probabilistic belief about its position. Planning in these domains requires computing the best trajectory through the space of possible beliefs. We show that planning in belief space can he done efficiently for linear Gaussian systems by using a factored form of the covariance matrix. This factored form allows several prediction and measurement steps to be combined into a single linear transfer function, leading to very efficient posterior belief prediction during planning. We give a belief-space variant of the Probabilistic Roadmap algorithm called the Belief Roadmap (BRM) and show that the BRM can compute plans substantially faster than conventional belief space planning. We also show performance results for planning a path across MIT campus without perfect localization.
A major unsolved problem is to provide robots with sufficient manual intelligence so that they can seamlessly interact with environments made for humans, where almost all objects have been designed for being acted upo...
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ISBN:
(纸本)9783642147432
A major unsolved problem is to provide robots with sufficient manual intelligence so that they can seamlessly interact with environments made for humans, where almost all objects have been designed for being acted upon by human hands. With the recent advent of anthropomorphic hand designs whose configuration space begins to approximate that of human hands in a realistic fashion, manual intelligence for robots is rapidly emerging as an exciting interdisciplinary research field, Connecting :robotics research with advances in the cognitive and brain sciences about the representation and production of dextrous motion. We argue that a thorough understanding of manual intelligence will be basic for our concepts of objects,actions. and the acquisition of new skills, while the rich grounding of manual intelligence in the physical level of interaction may make it much more approachable for analysis than other, "higher level" aspects of intelligence. Therefore, we envisage manual intelligence as a. "Rosetta stone" for robot cognition. To substantiate that claim, we present and discuss some of the manifold connections between manual actions and cognitive functions, review some recent developments and paradigm shifts in the field, discuss what we consider major challenges and point out promising directions for future research.
The increasing demand for physical interaction between humans and robots has led to an interest in robots that guarantee safe behavior when human contact occurs. However, attaining established levels of performance wh...
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ISBN:
(纸本)9783642001956
The increasing demand for physical interaction between humans and robots has led to an interest in robots that guarantee safe behavior when human contact occurs. However, attaining established levels of performance while ensuring safety creates formidable challenges in mechanical design, actuation, sensing and control. To promote safety without compromising performance, a human-friendly robotic arm has been developed using the concept of hybrid actuation. The new design employs high-power, low-impedance pneumatic artificial muscles augmented with small electrical actuators, distributed compact pressure regulators with proportional valves, and hollow plastic links. The experimental results show that significant performance improvement can be achieved with hybrid actuation over a system with pneumatic muscles alone. In this paper we evaluate the safety of the new robot arm through experiments and simulation, demonstrating that its inertia/power characteristics surpass those of previous human-friendly robots we have developed.
One of the ultimate goals in robotics is to make high-DOF robots work autonomously in unknown changing environments. However, motion planning in completely unknown environments is largely an open problem and poses man...
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ISBN:
(纸本)9783642003110
One of the ultimate goals in robotics is to make high-DOF robots work autonomously in unknown changing environments. However, motion planning in completely unknown environments is largely an open problem and poses many challenges. One challenge is that in such an environment, the configuration-time space (CT-space) of a robot is not known beforehand. This paper describes how guaranteed collision-free regions in the unknown CT-space can be discovered progressively via sensing in real time based on the concept dynamic envelope, which is not conservative, i.e., does not assume worst-case scenarios, and is robust to uncertainties in obstacle behaviors. The introduced method can be used in general by real-time motion planners for high-DOF robots to discover the existence of guaranteed collision-free future motions efficiently. The utility is further confirmed both in simulation and in real-world testing involving a 5-DOF robot manipulator.
Partially observable Markov decision processes (POMDPs) have been successfully applied to various robot motion planning tasks under uncertainty. However, most existing POMDP algorithms assume a discrete state space, w...
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ISBN:
(纸本)9783642174513
Partially observable Markov decision processes (POMDPs) have been successfully applied to various robot motion planning tasks under uncertainty. However, most existing POMDP algorithms assume a discrete state space, while the natural state space of a robot is often continuous. This paper presents Monte Carlo Value Iteration (MCVI) for continuous-state POMDPs. MCVI samples both a robot's state space and the corresponding belief space, and avoids inefficient a priori discretization of the state space as a grid. Both theoretical results and preliminary experimental results indicate that MCVI is a promising new approach for robot motion planning under uncertainty.
We present two path planning algorithms for mobile robots that are connected by cable to a fixed base. Our algorithms efficiently compute the shortest path and control strategy that lead the robot to the target locati...
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ISBN:
(纸本)9783642174513
We present two path planning algorithms for mobile robots that are connected by cable to a fixed base. Our algorithms efficiently compute the shortest path and control strategy that lead the robot to the target location considering cable length and obstacle interactions. First, we focus on cable-obstacle collisions. We introduce and formally analyze algorithms that build and search an overlapped configuration space manifold. Next, we present an extension that considers cable-robot collisions. All algorithms are experimentally validated using a real robot.
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