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Indoor robot navigating amidst humans with uncertainties and intents: A collision cone approachAuthor: Akhil Kumar Nagariya Date: 2017-07-27 Report no: IIIT/TH/2017/54 Advisor:Madhava Krishna AbstractAutonomous Navigation in indoor environment where human and robot occupy the same workspace is a challenging problem, robots should behave in a socially acceptable way otherwise they will cause discomfort for humans which could possibly lead to confusion and disastrous results. In recent years autonomous navigation systems have been a primary focus in robotics. A wheelchair is a mechanical device that can often assist people with disabilities. It comes under Rehabilitation Technologies or assistive technologies. It effectively uses wheels and mechanical support to overcome a loss of legs or leg control. Manual wheelchairs can be operated by persons who can use their upper body or someone available to assist. They can help people who have motor control problems, spinal injuries and amputation. An autonomous wheel chair can also help people who have lost motor control of their legs as well as their arms. They can help in moving patients in hospitals as well as moving heavy equipments in a warehouse like environment. The thesis contributes in the following ways. Firstly, we develop a wheel chair capable of autonomously navigating in an indoor environment. We also develop a novel approach to predict human intentions and introduce a probabilistic variant of time scaled collision cone constraints. These constraints allows us to relate space of collision free velocities to an associated confidence measure. Secondly, it develops an optimization framework for extracting a specific solution from the entire solution space of collision free velocities, depending on the factors such as distance from goal, probability of collision , robots kinematics and dynamic constraints such as turning radius, maximum acceleration and maximum velocity. Full thesis: pdf Centre for Robotics |
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