<p>The problem with motorized wheelchairs is that they are large, clumsy and difficult to control. This is especially true if the driver has severely reduced capabilities. What we want is a wheelchair that can take instructionsfrom the driver and then based on its understanding of the environment, construct a plan that will take the user to the intended destination. The user should be able to sit in a room, tell the wheelchair that he wants to be in another room and the wheelchair should take him there as quickly and smoothly as possible. </p><p>The planner presented in this thesis uses a randomized bi-directional tree search. It builds two trees, one from the start state and one from the goal state by randomly sampling the control space of the robot. Each node is a state and each edge is a control input to the robot.</p><p>In order to decrease the execution time and improve path quality, the planner uses several heuristics to guide the planner. The heuristics are based on Rapidly-exploring Random Trees, Probabilistic Road-maps and the gradient method. </p><p>For a normal household situation, this planner can construct a decent plan in mere seconds on relatively slow hardware. Most times it finishes in a fraction of a second. </p><p>This means that the planner has the ability to run in real-time. As a consequence, the planner can handle a dynamic environment, inaccurate sensor readings and an inaccurate physical robot model.</p>
| Identifer | oai:union.ndltd.org:UPSALLA/oai:DiVA.org:liu-2475 |
| Date | January 2004 |
| Creators | Edlund, Andreas |
| Publisher | Linköping University, Department of Electrical Engineering, Institutionen för systemteknik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, text |
| Relation | LiTH-ISY-Ex, ; 3567 |
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